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# Finetuned_Final_LM_200k_v2

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5769
- Accuracy: 0.8410
- F1: 0.8392
- Precision: 0.8573
- Recall: 0.8410

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.0074        | 0.08  | 500   | 1.2669          | 0.8482   | 0.8460 | 0.8695    | 0.8482 |
| 0.1731        | 0.16  | 1000  | 1.5018          | 0.8433   | 0.8411 | 0.8636    | 0.8433 |
| 0.2369        | 0.24  | 1500  | 2.0563          | 0.8486   | 0.8461 | 0.8721    | 0.8486 |
| 0.449         | 0.32  | 2000  | 2.4474          | 0.8323   | 0.8301 | 0.8511    | 0.8323 |
| 0.225         | 0.4   | 2500  | 2.1554          | 0.8471   | 0.8450 | 0.8662    | 0.8471 |
| 0.2479        | 0.48  | 3000  | 2.3559          | 0.8455   | 0.8438 | 0.8618    | 0.8455 |
| 0.2345        | 0.56  | 3500  | 2.3197          | 0.8440   | 0.8419 | 0.8639    | 0.8440 |
| 0.2424        | 0.64  | 4000  | 2.2472          | 0.8414   | 0.8396 | 0.8571    | 0.8414 |
| 0.1264        | 0.72  | 4500  | 2.3584          | 0.8418   | 0.8398 | 0.8599    | 0.8418 |
| 0.2699        | 0.8   | 5000  | 2.3153          | 0.8437   | 0.8419 | 0.8600    | 0.8437 |
| 0.1399        | 0.88  | 5500  | 2.3416          | 0.8471   | 0.8450 | 0.8665    | 0.8471 |
| 0.3039        | 0.96  | 6000  | 2.4308          | 0.8448   | 0.8429 | 0.8620    | 0.8448 |
| 0.0499        | 1.04  | 6500  | 2.5017          | 0.8448   | 0.8428 | 0.8628    | 0.8448 |
| 0.1455        | 1.12  | 7000  | 2.5024          | 0.8444   | 0.8425 | 0.8618    | 0.8444 |
| 0.3358        | 1.2   | 7500  | 2.3806          | 0.8425   | 0.8405 | 0.8609    | 0.8425 |
| 0.1951        | 1.28  | 8000  | 2.5782          | 0.8433   | 0.8415 | 0.8592    | 0.8433 |
| 0.2118        | 1.36  | 8500  | 2.5075          | 0.8429   | 0.8410 | 0.8597    | 0.8429 |
| 0.3137        | 1.44  | 9000  | 2.5662          | 0.8421   | 0.8403 | 0.8584    | 0.8421 |
| 0.1125        | 1.52  | 9500  | 2.5881          | 0.8425   | 0.8406 | 0.8602    | 0.8425 |
| 0.1198        | 1.6   | 10000 | 2.5321          | 0.8418   | 0.8400 | 0.8576    | 0.8418 |
| 0.2385        | 1.68  | 10500 | 2.5769          | 0.8410   | 0.8392 | 0.8573    | 0.8410 |


### 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_v2", "results": []}]}
transformers safetensors roberta text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us