
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# scenario-KD-PO-MSV-EN-D2-data-cl-massive-all_1.1

This model is a fine-tuned version of [haryoaw/scenario-TCR-data-cl-massive-all_1.1](https://huggingface.co/haryoaw/scenario-TCR-data-cl-massive-all_1.1) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1229
- Accuracy: 0.6899
- F1: 0.6367

## 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: 32
- seed: 42
- 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 | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 360  | 3.4927          | 0.6548   | 0.5984 |
| 1.7843        | 2.0   | 720  | 3.1582          | 0.6832   | 0.6253 |
| 0.8795        | 3.0   | 1080 | 3.1488          | 0.6835   | 0.6281 |
| 0.8795        | 4.0   | 1440 | 3.1525          | 0.6874   | 0.6338 |
| 0.6179        | 5.0   | 1800 | 3.1229          | 0.6899   | 0.6367 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.1.1+cu121
- Datasets 2.14.5
- Tokenizers 0.13.3

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["massive"], "metrics": ["accuracy", "f1"], "base_model": "haryoaw/scenario-TCR-data-cl-massive-all_1.1", "model-index": [{"name": "scenario-KD-PO-MSV-EN-D2-data-cl-massive-all_1.1", "results": []}]}
transformers pytorch xlm-roberta generated_from_trainer dataset:massive base_model:haryoaw/scenario-TCR-data-cl-massive-all_1.1 license:mit endpoints_compatible region:us