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distillbert_conv_quality_score

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  1. README.md +79 -0
  2. config.json +31 -0
  3. pytorch_model.bin +3 -0
  4. runs/1678549443.9220474/events.out.tfevents.1678549443.irliotggpu01.697833.1 +3 -0
  5. runs/1678549443.9255106/hparams.yml +8 -0
  6. runs/events.out.tfevents.1678549443.irliotggpu01.697833.0 +3 -0
  7. special_tokens_map.json +7 -0
  8. tokenizer.json +0 -0
  9. tokenizer_config.json +14 -0
  10. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - transformers
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+ - pytorch
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+ datasets:
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+ - conv_ai_2
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+ model-index:
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+ - name: distillbert_conv_quality_score
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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 Keras had access to. You should
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+ probably proofread and complete it, then remove this comment. -->
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+
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+ # distillbert_conv_quality_score
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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 conv_ai_2 dataset.
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+ It achieves the following results on the evaluation set:
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+ - training/loss: 0.0165
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+ - validation/loss: 0.0149
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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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+ - epochs: 40
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+ - batch_size: 16
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+ - learning_rate: 0.0002
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+ - eval_steps: 82
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+ - log_steps: 82
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+ - save_steps: 41
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+ - gradient_accumulation_steps: 1
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+ - warmup_steps: 0
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+
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+ ### Training results
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+
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+ | step | training/loss | validation/loss |
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+ |:----:|:-------------:|:---------------:|
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+ | 81 | 0.1020 | 0.0794 |
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+ | 163 | 0.0800 | 0.0713 |
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+ | 245 | 0.0553 | 0.0491 |
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+ | 327 | 0.0362 | 0.0440 |
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+ | 409 | 0.0282 | 0.0352 |
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+ | 491 | 0.0282 | 0.0412 |
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+ | 573 | 0.0256 | 0.0293 |
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+ | 655 | 0.0238 | 0.0252 |
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+ | 737 | 0.0175 | 0.0226 |
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+ | 819 | 0.0154 | 0.0228 |
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+ | 901 | 0.0116 | 0.0205 |
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+ | 983 | 0.0160 | 0.0202 |
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+ | 1065 | 0.0146 | 0.0240 |
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+ | 1147 | 0.0182 | 0.0180 |
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+ | 1229 | 0.0171 | 0.0192 |
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+ | 1311 | 0.0091 | 0.0174 |
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+ | 1393 | 0.0171 | 0.0158 |
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+ | 1475 | 0.0137 | 0.0158 |
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+ | 1557 | 0.0158 | 0.0148 |
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+ | 1639 | 0.0165 | 0.0149 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.1
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+ - Datasets 2.10.1
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+ - Tokenizers 0.13.2
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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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+ "DistilBertForSequenceClassification"
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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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+ "hidden_dim": 3072,
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+ "id2label": {
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+ "0": "LABEL_0"
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+ },
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+ "initializer_range": 0.02,
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+ "label2id": {
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+ },
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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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+ "problem_type": "regression",
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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": "4.26.1",
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+ "vocab_size": 30522
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+ }
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+ batch_size: 16
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+ epochs: 40
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+ eval_steps: 82
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+ gradient_accumulation_steps: 1
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+ learning_rate: 0.0002
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+ log_steps: 82
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+ save_steps: 41
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+ warmup_steps: 0
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tokenizer_config.json ADDED
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+ {
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