End of training
Browse files- README.md +71 -70
- config.json +33 -33
- model.safetensors +1 -1
- runs/Sep29_21-15-50_DESKTOP-P79TL96/events.out.tfevents.1727662555.DESKTOP-P79TL96 +3 -0
- special_tokens_map.json +7 -7
- tokenizer_config.json +55 -55
- training_args.bin +2 -2
README.md
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---
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---
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library_name: transformers
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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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metrics:
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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: Distilbert
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results: []
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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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# Distilbert
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6418
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- Accuracy: 0.7992
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- F1: 0.7411
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- Precision: 0.7935
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- Recall: 0.6952
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 32
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- eval_batch_size: 16
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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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.6496 | 1.0 | 32 | 0.5694 | 0.6811 | 0.5888 | 0.6304 | 0.5524 |
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| 0.4365 | 2.0 | 64 | 0.5541 | 0.7441 | 0.6409 | 0.7632 | 0.5524 |
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| 0.2431 | 3.0 | 96 | 0.5720 | 0.7795 | 0.7282 | 0.7426 | 0.7143 |
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| 0.1262 | 4.0 | 128 | 0.5727 | 0.7874 | 0.7429 | 0.7429 | 0.7429 |
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| 0.0742 | 5.0 | 160 | 0.6418 | 0.7992 | 0.7411 | 0.7935 | 0.6952 |
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### Framework versions
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- Transformers 4.45.1
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- Pytorch 2.4.0
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- Datasets 2.20.0
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- Tokenizers 0.20.0
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config.json
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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": "NEGATIVE",
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"1": "POSITIVE"
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},
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"initializer_range": 0.02,
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"label2id": {
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"NEGATIVE": 0,
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"POSITIVE": 1
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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": "single_label_classification",
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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.
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"vocab_size": 30522
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}
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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": "NEGATIVE",
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"1": "POSITIVE"
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"initializer_range": 0.02,
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"label2id": {
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"NEGATIVE": 0,
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"POSITIVE": 1
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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": "single_label_classification",
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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": "4.45.1",
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"vocab_size": 30522
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}
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model.safetensors
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special_tokens_map.json
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{
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"cls_token": "[CLS]",
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tokenizer_config.json
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training_args.bin
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