yalhessi commited on
Commit
4c992d8
·
verified ·
1 Parent(s): c760eed

Training in progress, epoch 6, checkpoint

Browse files
checkpoint-21594/README.md ADDED
@@ -0,0 +1,202 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: deepseek-ai/deepseek-coder-1.3b-base
3
+ library_name: peft
4
+ ---
5
+
6
+ # Model Card for Model ID
7
+
8
+ <!-- Provide a quick summary of what the model is/does. -->
9
+
10
+
11
+
12
+ ## Model Details
13
+
14
+ ### Model Description
15
+
16
+ <!-- Provide a longer summary of what this model is. -->
17
+
18
+
19
+
20
+ - **Developed by:** [More Information Needed]
21
+ - **Funded by [optional]:** [More Information Needed]
22
+ - **Shared by [optional]:** [More Information Needed]
23
+ - **Model type:** [More Information Needed]
24
+ - **Language(s) (NLP):** [More Information Needed]
25
+ - **License:** [More Information Needed]
26
+ - **Finetuned from model [optional]:** [More Information Needed]
27
+
28
+ ### Model Sources [optional]
29
+
30
+ <!-- Provide the basic links for the model. -->
31
+
32
+ - **Repository:** [More Information Needed]
33
+ - **Paper [optional]:** [More Information Needed]
34
+ - **Demo [optional]:** [More Information Needed]
35
+
36
+ ## Uses
37
+
38
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
39
+
40
+ ### Direct Use
41
+
42
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
43
+
44
+ [More Information Needed]
45
+
46
+ ### Downstream Use [optional]
47
+
48
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
49
+
50
+ [More Information Needed]
51
+
52
+ ### Out-of-Scope Use
53
+
54
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
55
+
56
+ [More Information Needed]
57
+
58
+ ## Bias, Risks, and Limitations
59
+
60
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
61
+
62
+ [More Information Needed]
63
+
64
+ ### Recommendations
65
+
66
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
67
+
68
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
69
+
70
+ ## How to Get Started with the Model
71
+
72
+ Use the code below to get started with the model.
73
+
74
+ [More Information Needed]
75
+
76
+ ## Training Details
77
+
78
+ ### Training Data
79
+
80
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
81
+
82
+ [More Information Needed]
83
+
84
+ ### Training Procedure
85
+
86
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
87
+
88
+ #### Preprocessing [optional]
89
+
90
+ [More Information Needed]
91
+
92
+
93
+ #### Training Hyperparameters
94
+
95
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
96
+
97
+ #### Speeds, Sizes, Times [optional]
98
+
99
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
100
+
101
+ [More Information Needed]
102
+
103
+ ## Evaluation
104
+
105
+ <!-- This section describes the evaluation protocols and provides the results. -->
106
+
107
+ ### Testing Data, Factors & Metrics
108
+
109
+ #### Testing Data
110
+
111
+ <!-- This should link to a Dataset Card if possible. -->
112
+
113
+ [More Information Needed]
114
+
115
+ #### Factors
116
+
117
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
118
+
119
+ [More Information Needed]
120
+
121
+ #### Metrics
122
+
123
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
124
+
125
+ [More Information Needed]
126
+
127
+ ### Results
128
+
129
+ [More Information Needed]
130
+
131
+ #### Summary
132
+
133
+
134
+
135
+ ## Model Examination [optional]
136
+
137
+ <!-- Relevant interpretability work for the model goes here -->
138
+
139
+ [More Information Needed]
140
+
141
+ ## Environmental Impact
142
+
143
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
144
+
145
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
146
+
147
+ - **Hardware Type:** [More Information Needed]
148
+ - **Hours used:** [More Information Needed]
149
+ - **Cloud Provider:** [More Information Needed]
150
+ - **Compute Region:** [More Information Needed]
151
+ - **Carbon Emitted:** [More Information Needed]
152
+
153
+ ## Technical Specifications [optional]
154
+
155
+ ### Model Architecture and Objective
156
+
157
+ [More Information Needed]
158
+
159
+ ### Compute Infrastructure
160
+
161
+ [More Information Needed]
162
+
163
+ #### Hardware
164
+
165
+ [More Information Needed]
166
+
167
+ #### Software
168
+
169
+ [More Information Needed]
170
+
171
+ ## Citation [optional]
172
+
173
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
174
+
175
+ **BibTeX:**
176
+
177
+ [More Information Needed]
178
+
179
+ **APA:**
180
+
181
+ [More Information Needed]
182
+
183
+ ## Glossary [optional]
184
+
185
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
186
+
187
+ [More Information Needed]
188
+
189
+ ## More Information [optional]
190
+
191
+ [More Information Needed]
192
+
193
+ ## Model Card Authors [optional]
194
+
195
+ [More Information Needed]
196
+
197
+ ## Model Card Contact
198
+
199
+ [More Information Needed]
200
+ ### Framework versions
201
+
202
+ - PEFT 0.14.0
checkpoint-21594/adapter_config.json ADDED
@@ -0,0 +1,32 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alpha_pattern": {},
3
+ "auto_mapping": null,
4
+ "base_model_name_or_path": "deepseek-ai/deepseek-coder-1.3b-base",
5
+ "bias": "none",
6
+ "eva_config": null,
7
+ "exclude_modules": null,
8
+ "fan_in_fan_out": false,
9
+ "inference_mode": true,
10
+ "init_lora_weights": true,
11
+ "layer_replication": null,
12
+ "layers_pattern": null,
13
+ "layers_to_transform": null,
14
+ "loftq_config": {},
15
+ "lora_alpha": 32,
16
+ "lora_bias": false,
17
+ "lora_dropout": 0.05,
18
+ "megatron_config": null,
19
+ "megatron_core": "megatron.core",
20
+ "modules_to_save": null,
21
+ "peft_type": "LORA",
22
+ "r": 8,
23
+ "rank_pattern": {},
24
+ "revision": null,
25
+ "target_modules": [
26
+ "q_proj",
27
+ "v_proj"
28
+ ],
29
+ "task_type": "CAUSAL_LM",
30
+ "use_dora": false,
31
+ "use_rslora": false
32
+ }
checkpoint-21594/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:cf327c34636c9906364103a8865c69555f171f9652ec0480b77b8ccaf7b661a2
3
+ size 268636736
checkpoint-21594/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e43d3422e9d874ab53b04222950c9d0689605a67ac4fcb02428e4d46ca569270
3
+ size 12663802
checkpoint-21594/rng_state_0.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:aa095e38d398d2eef3e07c0994b65ee6b5cb6b09b34415e3eb7b6664350f0b26
3
+ size 15984
checkpoint-21594/rng_state_1.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:6c6cf284249d3231fced7fd176d6903f67a56cc778b716630b4bc930bdc2c787
3
+ size 15984
checkpoint-21594/rng_state_2.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:46443c60a73e22dceccd50e469f93a775ea8d3c73388d522da0b5aad9bfc824e
3
+ size 15984
checkpoint-21594/rng_state_3.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:161b7e4563f351991b095e91ff951fbf4125309a2c53eff06743d90162e3c2dd
3
+ size 15984
checkpoint-21594/rng_state_4.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c4294476ec90c0fd53be6b93215683c5dc0ae7a4c45e3bc1dee004a56b665d7f
3
+ size 15984
checkpoint-21594/rng_state_5.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:90433f394ea97bd33472ad69a25f61625057c2882c74c37ed954a798be485c0c
3
+ size 15984
checkpoint-21594/rng_state_6.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c31ee4eb352bd2826fd09654f8e2a65c092e72010b96328fb8c2c24ae81da549
3
+ size 15984
checkpoint-21594/rng_state_7.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3d7ba8e9028d3688c325ec1615d8cd521efd90834f8c9ad8d43e819ae5a3a200
3
+ size 15984
checkpoint-21594/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:692cb860d5f3ad084c9878a810a0bb25f098b722d607dc1a4fd1a6ac4791fe89
3
+ size 1064
checkpoint-21594/trainer_state.json ADDED
@@ -0,0 +1,566 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_metric": null,
3
+ "best_model_checkpoint": null,
4
+ "epoch": 6.0,
5
+ "eval_steps": 720,
6
+ "global_step": 21594,
7
+ "is_hyper_param_search": false,
8
+ "is_local_process_zero": true,
9
+ "is_world_process_zero": true,
10
+ "log_history": [
11
+ {
12
+ "epoch": 0.13892747985551543,
13
+ "grad_norm": 0.8139383792877197,
14
+ "learning_rate": 0.0007907937390015746,
15
+ "loss": 0.43,
16
+ "step": 500
17
+ },
18
+ {
19
+ "epoch": 0.2000555709919422,
20
+ "eval_loss": 0.34008777141571045,
21
+ "eval_runtime": 5.5933,
22
+ "eval_samples_per_second": 89.392,
23
+ "eval_steps_per_second": 5.721,
24
+ "step": 720
25
+ },
26
+ {
27
+ "epoch": 0.27785495971103086,
28
+ "grad_norm": 0.9147945642471313,
29
+ "learning_rate": 0.0007815319070112068,
30
+ "loss": 0.3227,
31
+ "step": 1000
32
+ },
33
+ {
34
+ "epoch": 0.4001111419838844,
35
+ "eval_loss": 0.29102692008018494,
36
+ "eval_runtime": 5.6203,
37
+ "eval_samples_per_second": 88.964,
38
+ "eval_steps_per_second": 5.694,
39
+ "step": 1440
40
+ },
41
+ {
42
+ "epoch": 0.41678243956654626,
43
+ "grad_norm": 0.7195032238960266,
44
+ "learning_rate": 0.0007722885986848199,
45
+ "loss": 0.2976,
46
+ "step": 1500
47
+ },
48
+ {
49
+ "epoch": 0.5557099194220617,
50
+ "grad_norm": 0.7690744400024414,
51
+ "learning_rate": 0.0007630267666944522,
52
+ "loss": 0.2819,
53
+ "step": 2000
54
+ },
55
+ {
56
+ "epoch": 0.6001667129758266,
57
+ "eval_loss": 0.27511677145957947,
58
+ "eval_runtime": 5.6033,
59
+ "eval_samples_per_second": 89.233,
60
+ "eval_steps_per_second": 5.711,
61
+ "step": 2160
62
+ },
63
+ {
64
+ "epoch": 0.6946373992775771,
65
+ "grad_norm": 0.9451383352279663,
66
+ "learning_rate": 0.0007537649347040845,
67
+ "loss": 0.2714,
68
+ "step": 2500
69
+ },
70
+ {
71
+ "epoch": 0.8002222839677688,
72
+ "eval_loss": 0.26355135440826416,
73
+ "eval_runtime": 5.5717,
74
+ "eval_samples_per_second": 89.739,
75
+ "eval_steps_per_second": 5.743,
76
+ "step": 2880
77
+ },
78
+ {
79
+ "epoch": 0.8335648791330925,
80
+ "grad_norm": 0.6594133973121643,
81
+ "learning_rate": 0.0007445031027137167,
82
+ "loss": 0.2633,
83
+ "step": 3000
84
+ },
85
+ {
86
+ "epoch": 0.972492358988608,
87
+ "grad_norm": 0.7951074838638306,
88
+ "learning_rate": 0.0007352412707233491,
89
+ "loss": 0.2595,
90
+ "step": 3500
91
+ },
92
+ {
93
+ "epoch": 1.000277854959711,
94
+ "eval_loss": 0.2652628719806671,
95
+ "eval_runtime": 5.6216,
96
+ "eval_samples_per_second": 88.942,
97
+ "eval_steps_per_second": 5.692,
98
+ "step": 3600
99
+ },
100
+ {
101
+ "epoch": 1.1114198388441234,
102
+ "grad_norm": 0.6959578990936279,
103
+ "learning_rate": 0.0007259794387329814,
104
+ "loss": 0.2446,
105
+ "step": 4000
106
+ },
107
+ {
108
+ "epoch": 1.2003334259516532,
109
+ "eval_loss": 0.26396042108535767,
110
+ "eval_runtime": 5.6294,
111
+ "eval_samples_per_second": 88.819,
112
+ "eval_steps_per_second": 5.684,
113
+ "step": 4320
114
+ },
115
+ {
116
+ "epoch": 1.2503473186996388,
117
+ "grad_norm": 0.5934865474700928,
118
+ "learning_rate": 0.0007167361304065945,
119
+ "loss": 0.2432,
120
+ "step": 4500
121
+ },
122
+ {
123
+ "epoch": 1.3892747985551543,
124
+ "grad_norm": 0.681597888469696,
125
+ "learning_rate": 0.0007074742984162268,
126
+ "loss": 0.2403,
127
+ "step": 5000
128
+ },
129
+ {
130
+ "epoch": 1.4003889969435954,
131
+ "eval_loss": 0.24760469794273376,
132
+ "eval_runtime": 5.6222,
133
+ "eval_samples_per_second": 88.933,
134
+ "eval_steps_per_second": 5.692,
135
+ "step": 5040
136
+ },
137
+ {
138
+ "epoch": 1.5282022784106695,
139
+ "grad_norm": 0.7086077928543091,
140
+ "learning_rate": 0.000698212466425859,
141
+ "loss": 0.2347,
142
+ "step": 5500
143
+ },
144
+ {
145
+ "epoch": 1.6004445679355377,
146
+ "eval_loss": 0.24589040875434875,
147
+ "eval_runtime": 5.6296,
148
+ "eval_samples_per_second": 88.816,
149
+ "eval_steps_per_second": 5.684,
150
+ "step": 5760
151
+ },
152
+ {
153
+ "epoch": 1.667129758266185,
154
+ "grad_norm": 0.6966447830200195,
155
+ "learning_rate": 0.0006889506344354914,
156
+ "loss": 0.235,
157
+ "step": 6000
158
+ },
159
+ {
160
+ "epoch": 1.8005001389274797,
161
+ "eval_loss": 0.2404348999261856,
162
+ "eval_runtime": 5.6722,
163
+ "eval_samples_per_second": 88.149,
164
+ "eval_steps_per_second": 5.642,
165
+ "step": 6480
166
+ },
167
+ {
168
+ "epoch": 1.8060572381217006,
169
+ "grad_norm": 0.7572044134140015,
170
+ "learning_rate": 0.0006796888024451237,
171
+ "loss": 0.2302,
172
+ "step": 6500
173
+ },
174
+ {
175
+ "epoch": 1.9449847179772157,
176
+ "grad_norm": 0.5248509049415588,
177
+ "learning_rate": 0.0006704269704547561,
178
+ "loss": 0.2278,
179
+ "step": 7000
180
+ },
181
+ {
182
+ "epoch": 2.000555709919422,
183
+ "eval_loss": 0.23613983392715454,
184
+ "eval_runtime": 5.6434,
185
+ "eval_samples_per_second": 88.599,
186
+ "eval_steps_per_second": 5.67,
187
+ "step": 7200
188
+ },
189
+ {
190
+ "epoch": 2.0839121978327313,
191
+ "grad_norm": 0.6326273083686829,
192
+ "learning_rate": 0.0006611651384643883,
193
+ "loss": 0.2191,
194
+ "step": 7500
195
+ },
196
+ {
197
+ "epoch": 2.2006112809113643,
198
+ "eval_loss": 0.23707860708236694,
199
+ "eval_runtime": 5.616,
200
+ "eval_samples_per_second": 89.032,
201
+ "eval_steps_per_second": 5.698,
202
+ "step": 7920
203
+ },
204
+ {
205
+ "epoch": 2.222839677688247,
206
+ "grad_norm": 1.276680827140808,
207
+ "learning_rate": 0.0006519033064740205,
208
+ "loss": 0.2164,
209
+ "step": 8000
210
+ },
211
+ {
212
+ "epoch": 2.361767157543762,
213
+ "grad_norm": 0.5319393873214722,
214
+ "learning_rate": 0.0006426414744836529,
215
+ "loss": 0.2162,
216
+ "step": 8500
217
+ },
218
+ {
219
+ "epoch": 2.4006668519033063,
220
+ "eval_loss": 0.2294686734676361,
221
+ "eval_runtime": 5.6559,
222
+ "eval_samples_per_second": 88.404,
223
+ "eval_steps_per_second": 5.658,
224
+ "step": 8640
225
+ },
226
+ {
227
+ "epoch": 2.5006946373992776,
228
+ "grad_norm": 1.0233811140060425,
229
+ "learning_rate": 0.000633398166157266,
230
+ "loss": 0.2117,
231
+ "step": 9000
232
+ },
233
+ {
234
+ "epoch": 2.600722422895249,
235
+ "eval_loss": 0.22413167357444763,
236
+ "eval_runtime": 5.687,
237
+ "eval_samples_per_second": 87.92,
238
+ "eval_steps_per_second": 5.627,
239
+ "step": 9360
240
+ },
241
+ {
242
+ "epoch": 2.639622117254793,
243
+ "grad_norm": 0.7024723887443542,
244
+ "learning_rate": 0.0006241363341668982,
245
+ "loss": 0.2107,
246
+ "step": 9500
247
+ },
248
+ {
249
+ "epoch": 2.7785495971103087,
250
+ "grad_norm": 0.7756719589233398,
251
+ "learning_rate": 0.0006148745021765306,
252
+ "loss": 0.2106,
253
+ "step": 10000
254
+ },
255
+ {
256
+ "epoch": 2.800777993887191,
257
+ "eval_loss": 0.22200989723205566,
258
+ "eval_runtime": 5.6306,
259
+ "eval_samples_per_second": 88.8,
260
+ "eval_steps_per_second": 5.683,
261
+ "step": 10080
262
+ },
263
+ {
264
+ "epoch": 2.917477076965824,
265
+ "grad_norm": 0.5662937164306641,
266
+ "learning_rate": 0.0006056126701861628,
267
+ "loss": 0.2112,
268
+ "step": 10500
269
+ },
270
+ {
271
+ "epoch": 3.000833564879133,
272
+ "eval_loss": 0.218927264213562,
273
+ "eval_runtime": 5.6534,
274
+ "eval_samples_per_second": 88.443,
275
+ "eval_steps_per_second": 5.66,
276
+ "step": 10800
277
+ },
278
+ {
279
+ "epoch": 3.0564045568213394,
280
+ "grad_norm": 0.7616448998451233,
281
+ "learning_rate": 0.0005963508381957952,
282
+ "loss": 0.2034,
283
+ "step": 11000
284
+ },
285
+ {
286
+ "epoch": 3.1953320366768545,
287
+ "grad_norm": 0.552426278591156,
288
+ "learning_rate": 0.0005871075298694081,
289
+ "loss": 0.1977,
290
+ "step": 11500
291
+ },
292
+ {
293
+ "epoch": 3.2008891358710754,
294
+ "eval_loss": 0.22195962071418762,
295
+ "eval_runtime": 5.6319,
296
+ "eval_samples_per_second": 88.78,
297
+ "eval_steps_per_second": 5.682,
298
+ "step": 11520
299
+ },
300
+ {
301
+ "epoch": 3.33425951653237,
302
+ "grad_norm": 0.5001489520072937,
303
+ "learning_rate": 0.0005778456978790405,
304
+ "loss": 0.1992,
305
+ "step": 12000
306
+ },
307
+ {
308
+ "epoch": 3.4009447068630174,
309
+ "eval_loss": 0.2205904722213745,
310
+ "eval_runtime": 5.6756,
311
+ "eval_samples_per_second": 88.096,
312
+ "eval_steps_per_second": 5.638,
313
+ "step": 12240
314
+ },
315
+ {
316
+ "epoch": 3.4731869963878856,
317
+ "grad_norm": 0.9021688103675842,
318
+ "learning_rate": 0.0005685838658886728,
319
+ "loss": 0.1942,
320
+ "step": 12500
321
+ },
322
+ {
323
+ "epoch": 3.6010002778549595,
324
+ "eval_loss": 0.21617579460144043,
325
+ "eval_runtime": 5.6193,
326
+ "eval_samples_per_second": 88.979,
327
+ "eval_steps_per_second": 5.695,
328
+ "step": 12960
329
+ },
330
+ {
331
+ "epoch": 3.612114476243401,
332
+ "grad_norm": 0.7987478971481323,
333
+ "learning_rate": 0.0005593220338983052,
334
+ "loss": 0.1966,
335
+ "step": 13000
336
+ },
337
+ {
338
+ "epoch": 3.7510419560989163,
339
+ "grad_norm": 0.7092472910881042,
340
+ "learning_rate": 0.0005500602019079374,
341
+ "loss": 0.1937,
342
+ "step": 13500
343
+ },
344
+ {
345
+ "epoch": 3.801055848846902,
346
+ "eval_loss": 0.21359983086585999,
347
+ "eval_runtime": 5.6236,
348
+ "eval_samples_per_second": 88.911,
349
+ "eval_steps_per_second": 5.69,
350
+ "step": 13680
351
+ },
352
+ {
353
+ "epoch": 3.889969435954432,
354
+ "grad_norm": 0.8303009867668152,
355
+ "learning_rate": 0.0005407983699175697,
356
+ "loss": 0.1947,
357
+ "step": 14000
358
+ },
359
+ {
360
+ "epoch": 4.001111419838844,
361
+ "eval_loss": 0.2068374752998352,
362
+ "eval_runtime": 5.6571,
363
+ "eval_samples_per_second": 88.384,
364
+ "eval_steps_per_second": 5.657,
365
+ "step": 14400
366
+ },
367
+ {
368
+ "epoch": 4.0288969158099475,
369
+ "grad_norm": 1.5833752155303955,
370
+ "learning_rate": 0.000531536537927202,
371
+ "loss": 0.1891,
372
+ "step": 14500
373
+ },
374
+ {
375
+ "epoch": 4.167824395665463,
376
+ "grad_norm": 0.7455429434776306,
377
+ "learning_rate": 0.0005222932296008151,
378
+ "loss": 0.1813,
379
+ "step": 15000
380
+ },
381
+ {
382
+ "epoch": 4.201166990830786,
383
+ "eval_loss": 0.20782814919948578,
384
+ "eval_runtime": 5.6478,
385
+ "eval_samples_per_second": 88.53,
386
+ "eval_steps_per_second": 5.666,
387
+ "step": 15120
388
+ },
389
+ {
390
+ "epoch": 4.306751875520978,
391
+ "grad_norm": 0.6294922828674316,
392
+ "learning_rate": 0.0005130313976104474,
393
+ "loss": 0.1831,
394
+ "step": 15500
395
+ },
396
+ {
397
+ "epoch": 4.4012225618227285,
398
+ "eval_loss": 0.2086438238620758,
399
+ "eval_runtime": 5.6291,
400
+ "eval_samples_per_second": 88.823,
401
+ "eval_steps_per_second": 5.685,
402
+ "step": 15840
403
+ },
404
+ {
405
+ "epoch": 4.445679355376494,
406
+ "grad_norm": 0.4998241066932678,
407
+ "learning_rate": 0.0005037695656200797,
408
+ "loss": 0.1839,
409
+ "step": 16000
410
+ },
411
+ {
412
+ "epoch": 4.584606835232009,
413
+ "grad_norm": 0.6332064867019653,
414
+ "learning_rate": 0.0004945077336297119,
415
+ "loss": 0.18,
416
+ "step": 16500
417
+ },
418
+ {
419
+ "epoch": 4.601278132814671,
420
+ "eval_loss": 0.20396389067173004,
421
+ "eval_runtime": 5.6464,
422
+ "eval_samples_per_second": 88.553,
423
+ "eval_steps_per_second": 5.667,
424
+ "step": 16560
425
+ },
426
+ {
427
+ "epoch": 4.723534315087524,
428
+ "grad_norm": 0.8065542578697205,
429
+ "learning_rate": 0.0004852459016393443,
430
+ "loss": 0.1805,
431
+ "step": 17000
432
+ },
433
+ {
434
+ "epoch": 4.801333703806613,
435
+ "eval_loss": 0.21260568499565125,
436
+ "eval_runtime": 5.6233,
437
+ "eval_samples_per_second": 88.915,
438
+ "eval_steps_per_second": 5.691,
439
+ "step": 17280
440
+ },
441
+ {
442
+ "epoch": 4.86246179494304,
443
+ "grad_norm": 0.49171850085258484,
444
+ "learning_rate": 0.00047600259331295736,
445
+ "loss": 0.1809,
446
+ "step": 17500
447
+ },
448
+ {
449
+ "epoch": 5.001389274798555,
450
+ "grad_norm": 0.6531211137771606,
451
+ "learning_rate": 0.0004667407613225896,
452
+ "loss": 0.177,
453
+ "step": 18000
454
+ },
455
+ {
456
+ "epoch": 5.001389274798555,
457
+ "eval_loss": 0.2037501484155655,
458
+ "eval_runtime": 5.6532,
459
+ "eval_samples_per_second": 88.446,
460
+ "eval_steps_per_second": 5.661,
461
+ "step": 18000
462
+ },
463
+ {
464
+ "epoch": 5.14031675465407,
465
+ "grad_norm": 0.5100106596946716,
466
+ "learning_rate": 0.0004574789293322219,
467
+ "loss": 0.1662,
468
+ "step": 18500
469
+ },
470
+ {
471
+ "epoch": 5.201444845790498,
472
+ "eval_loss": 0.20373231172561646,
473
+ "eval_runtime": 5.6571,
474
+ "eval_samples_per_second": 88.385,
475
+ "eval_steps_per_second": 5.657,
476
+ "step": 18720
477
+ },
478
+ {
479
+ "epoch": 5.279244234509586,
480
+ "grad_norm": 0.6745024919509888,
481
+ "learning_rate": 0.00044821709734185424,
482
+ "loss": 0.1665,
483
+ "step": 19000
484
+ },
485
+ {
486
+ "epoch": 5.401500416782439,
487
+ "eval_loss": 0.20096533000469208,
488
+ "eval_runtime": 5.6324,
489
+ "eval_samples_per_second": 88.772,
490
+ "eval_steps_per_second": 5.681,
491
+ "step": 19440
492
+ },
493
+ {
494
+ "epoch": 5.418171714365101,
495
+ "grad_norm": 0.656152606010437,
496
+ "learning_rate": 0.0004389552653514866,
497
+ "loss": 0.1673,
498
+ "step": 19500
499
+ },
500
+ {
501
+ "epoch": 5.5570991942206165,
502
+ "grad_norm": 0.7765993475914001,
503
+ "learning_rate": 0.0004296934333611189,
504
+ "loss": 0.1682,
505
+ "step": 20000
506
+ },
507
+ {
508
+ "epoch": 5.601555987774382,
509
+ "eval_loss": 0.19679580628871918,
510
+ "eval_runtime": 5.6341,
511
+ "eval_samples_per_second": 88.746,
512
+ "eval_steps_per_second": 5.68,
513
+ "step": 20160
514
+ },
515
+ {
516
+ "epoch": 5.6960266740761325,
517
+ "grad_norm": 0.8163785934448242,
518
+ "learning_rate": 0.00042043160137075113,
519
+ "loss": 0.1686,
520
+ "step": 20500
521
+ },
522
+ {
523
+ "epoch": 5.801611558766324,
524
+ "eval_loss": 0.192356139421463,
525
+ "eval_runtime": 5.6283,
526
+ "eval_samples_per_second": 88.836,
527
+ "eval_steps_per_second": 5.686,
528
+ "step": 20880
529
+ },
530
+ {
531
+ "epoch": 5.834954153931648,
532
+ "grad_norm": 0.8751519918441772,
533
+ "learning_rate": 0.0004111882930443642,
534
+ "loss": 0.1664,
535
+ "step": 21000
536
+ },
537
+ {
538
+ "epoch": 5.973881633787163,
539
+ "grad_norm": 0.8651531934738159,
540
+ "learning_rate": 0.0004019264610539965,
541
+ "loss": 0.164,
542
+ "step": 21500
543
+ }
544
+ ],
545
+ "logging_steps": 500,
546
+ "max_steps": 43188,
547
+ "num_input_tokens_seen": 0,
548
+ "num_train_epochs": 12,
549
+ "save_steps": 500,
550
+ "stateful_callbacks": {
551
+ "TrainerControl": {
552
+ "args": {
553
+ "should_epoch_stop": false,
554
+ "should_evaluate": false,
555
+ "should_log": false,
556
+ "should_save": true,
557
+ "should_training_stop": false
558
+ },
559
+ "attributes": {}
560
+ }
561
+ },
562
+ "total_flos": 1.0580567090811372e+18,
563
+ "train_batch_size": 2,
564
+ "trial_name": null,
565
+ "trial_params": null
566
+ }
checkpoint-21594/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3f93d674e3d8f366a02faf7cb9762e951d43ff3aa54afd4529d34c17ca9d9e35
3
+ size 5496