End of training
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README.md
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---
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license: apache-2.0
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base_model: bert-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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- precision
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- recall
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- f1
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model-index:
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- name: test_trainer_full
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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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# test_trainer_full
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1544
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- Accuracy: 0.9614
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- Precision: 0.9394
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- Recall: 0.9575
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- F1: 0.9484
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- Roc Auc: 0.9911
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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: 2e-05
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- train_batch_size: 16
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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: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
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| 0.186 | 2.8571 | 500 | 0.1522 | 0.9614 | 0.9394 | 0.9575 | 0.9484 | 0.9911 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "bert-base-uncased",
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.41.2",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:3533d4b1ec5beb1c11b731ecb807013bd793a60463c7b95a351694fe139ea19e
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size 437958648
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runs/Jun11_20-05-11_d0f7c3cb197d/events.out.tfevents.1718136312.d0f7c3cb197d.172.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:4c24ec0f8638b23706ab0b4956d86bd8dd0c1cb6cacdc1d2adcbb5533b09fc16
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size 5888
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runs/Jun11_20-05-11_d0f7c3cb197d/events.out.tfevents.1718137163.d0f7c3cb197d.172.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:238b5cc32e76c130048a8fe5fd7468ed7ec9794a37bf3aba14be043e325ccae7
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size 611
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:4e69bbee4122347e479a05a6d707d60856c37a50c413ae75f6a3115d15631f08
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size 5112
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