transformers tensorboard safetensors bert token-classification generated_from_trainer base_model:salohnana2018/HARD_without_dp_6580_camel_prepocessed_OTE license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
base_model: salohnana2018/HARD_without_dp_6580_camel_prepocessed_OTE
model-index:
- name: OTE-DAPT-CAMEL-MSA-HARD-6580SUBSAMPLE-run1
  results: []
---

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# OTE-DAPT-CAMEL-MSA-HARD-6580SUBSAMPLE-run1

This model is a fine-tuned version of [salohnana2018/HARD_without_dp_6580_camel_prepocessed_OTE](https://huggingface.co/salohnana2018/HARD_without_dp_6580_camel_prepocessed_OTE) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1747
- Precision: 0.7539
- Recall: 0.7952
- F1: 0.7740
- Accuracy: 0.9544

## 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: 32
- eval_batch_size: 8
- seed: 25
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1466        | 1.0   | 121  | 0.1154          | 0.8219    | 0.7060 | 0.7596 | 0.9558   |
| 0.0871        | 2.0   | 242  | 0.1157          | 0.7818    | 0.7588 | 0.7702 | 0.9566   |
| 0.0585        | 3.0   | 363  | 0.1323          | 0.7773    | 0.7862 | 0.7818 | 0.9566   |
| 0.0365        | 4.0   | 484  | 0.1593          | 0.7434    | 0.7982 | 0.7698 | 0.9539   |
| 0.0248        | 5.0   | 605  | 0.1747          | 0.7539    | 0.7952 | 0.7740 | 0.9544   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
