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LightFury9
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nlp-mini-project

Token Classification
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distilbert
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End of training

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  1. README.md +84 -0
  2. config.json +53 -0
  3. model.safetensors +3 -0
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  13. special_tokens_map.json +7 -0
  14. tokenizer.json +0 -0
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  16. training_args.bin +3 -0
  17. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ language:
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+ - en
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+ license: apache-2.0
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+ base_model: distilbert-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: nlp-mini-prj
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # nlp-mini-prj
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0000
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 0.0841 | 3.76 | 500 | 0.0005 |
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+ | 0.0015 | 7.52 | 1000 | 0.0002 |
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+ | 0.0011 | 11.28 | 1500 | 0.0001 |
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+ | 0.0042 | 15.04 | 2000 | 0.0001 |
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+ | 0.0008 | 18.8 | 2500 | 0.0001 |
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+ | 0.0004 | 22.56 | 3000 | 0.0001 |
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+ | 0.0001 | 26.32 | 3500 | 0.0000 |
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+ | 0.0001 | 30.08 | 4000 | 0.0000 |
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+ | 0.0001 | 33.83 | 4500 | 0.0000 |
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+ | 0.0001 | 37.59 | 5000 | 0.0000 |
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+ | 0.0 | 41.35 | 5500 | 0.0000 |
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+ | 0.0 | 45.11 | 6000 | 0.0000 |
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+ | 0.0 | 48.87 | 6500 | 0.0000 |
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+ | 0.0 | 52.63 | 7000 | 0.0000 |
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+ | 0.0 | 56.39 | 7500 | 0.0000 |
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+ | 0.0 | 60.15 | 8000 | 0.0000 |
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+ | 0.0 | 63.91 | 8500 | 0.0000 |
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+ | 0.0 | 67.67 | 9000 | 0.0000 |
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+ | 0.0 | 71.43 | 9500 | 0.0000 |
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+ | 0.0 | 75.19 | 10000 | 0.0000 |
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+ | 0.0 | 78.95 | 10500 | 0.0000 |
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+ | 0.0 | 82.71 | 11000 | 0.0000 |
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+ | 0.0 | 86.47 | 11500 | 0.0000 |
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+ | 0.0 | 90.23 | 12000 | 0.0000 |
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+ | 0.0 | 93.98 | 12500 | 0.0000 |
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+ | 0.0 | 97.74 | 13000 | 0.0000 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0
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+ {
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+ "_name_or_path": "distilbert-base-uncased",
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+ "activation": "gelu",
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+ "architectures": [
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+ "DistilBertForTokenClassification"
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+ ],
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+ "attention_dropout": 0.1,
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+ "dim": 768,
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+ "dropout": 0.1,
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+ "finetuning_task": "ner",
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+ "id2label": {
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+ "max_position_embeddings": 512,
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+ "model_type": "distilbert",
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+ "n_heads": 12,
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+ "n_layers": 6,
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+ "pad_token_id": 0,
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+ "qa_dropout": 0.1,
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+ "seq_classif_dropout": 0.2,
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+ "sinusoidal_pos_embds": false,
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+ "tie_weights_": true,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.35.2",
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+ "vocab_size": 30522
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+ }
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