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# Finetuned_Final_LM_200k_v3

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4006
- Accuracy: 0.8429
- F1: 0.8410
- Precision: 0.8602
- Recall: 0.8429

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.038         | 0.08  | 500   | 1.6709          | 0.8505   | 0.8483 | 0.8713    | 0.8505 |
| 0.3847        | 0.16  | 1000  | 2.0643          | 0.8403   | 0.8385 | 0.8556    | 0.8403 |
| 0.4135        | 0.24  | 1500  | 1.7622          | 0.8429   | 0.8399 | 0.8706    | 0.8429 |
| 0.3496        | 0.32  | 2000  | 2.2005          | 0.8482   | 0.8459 | 0.8701    | 0.8482 |
| 0.2201        | 0.4   | 2500  | 2.2234          | 0.8467   | 0.8445 | 0.8673    | 0.8467 |
| 0.306         | 0.48  | 3000  | 2.0981          | 0.8395   | 0.8375 | 0.8567    | 0.8395 |
| 0.2741        | 0.56  | 3500  | 2.4972          | 0.8421   | 0.8401 | 0.8607    | 0.8421 |
| 0.2189        | 0.64  | 4000  | 2.1950          | 0.8459   | 0.8440 | 0.8641    | 0.8459 |
| 0.1442        | 0.72  | 4500  | 2.3179          | 0.8418   | 0.8399 | 0.8589    | 0.8418 |
| 0.3744        | 0.8   | 5000  | 2.3932          | 0.8395   | 0.8376 | 0.8565    | 0.8395 |
| 0.2153        | 0.88  | 5500  | 2.3213          | 0.8406   | 0.8384 | 0.8601    | 0.8406 |
| 0.3273        | 0.96  | 6000  | 2.2511          | 0.8467   | 0.8444 | 0.8682    | 0.8467 |
| 0.0371        | 1.04  | 6500  | 2.4062          | 0.8406   | 0.8388 | 0.8573    | 0.8406 |
| 0.1964        | 1.12  | 7000  | 2.3856          | 0.8421   | 0.8401 | 0.8604    | 0.8421 |
| 0.3516        | 1.2   | 7500  | 2.3023          | 0.8444   | 0.8424 | 0.8631    | 0.8444 |
| 0.1166        | 1.28  | 8000  | 2.3752          | 0.8414   | 0.8394 | 0.8594    | 0.8414 |
| 0.2922        | 1.36  | 8500  | 2.4364          | 0.8425   | 0.8405 | 0.8612    | 0.8425 |
| 0.2452        | 1.44  | 9000  | 2.3738          | 0.8421   | 0.8402 | 0.8599    | 0.8421 |
| 0.1247        | 1.52  | 9500  | 2.4287          | 0.8421   | 0.8401 | 0.8604    | 0.8421 |
| 0.0475        | 1.6   | 10000 | 2.4438          | 0.8433   | 0.8413 | 0.8610    | 0.8433 |
| 0.2052        | 1.68  | 10500 | 2.4006          | 0.8429   | 0.8410 | 0.8602    | 0.8429 |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1", "precision", "recall"], "model-index": [{"name": "Finetuned_Final_LM_200k_v3", "results": []}]}
transformers safetensors roberta text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us