---
license: mit
base_model: facebook/xlm-v-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-TCR-XLMV-XCOPA-2_data-xcopa_all
  results: []
---

<!-- 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-TCR-XLMV-XCOPA-2_data-xcopa_all

This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6931
- Accuracy: 0.5
- F1: 0.4671

## 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: 34
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 500

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.38  | 5    | 0.6932          | 0.4858   | 0.4767 |
| No log        | 0.77  | 10   | 0.6931          | 0.515    | 0.5134 |
| No log        | 1.15  | 15   | 0.6931          | 0.5158   | 0.5038 |
| No log        | 1.54  | 20   | 0.6931          | 0.5108   | 0.5021 |
| No log        | 1.92  | 25   | 0.6931          | 0.5217   | 0.5035 |
| No log        | 2.31  | 30   | 0.6931          | 0.525    | 0.5069 |
| No log        | 2.69  | 35   | 0.6931          | 0.5283   | 0.5070 |
| No log        | 3.08  | 40   | 0.6931          | 0.5292   | 0.5125 |
| No log        | 3.46  | 45   | 0.6931          | 0.5333   | 0.5122 |
| No log        | 3.85  | 50   | 0.6930          | 0.5125   | 0.4970 |
| No log        | 4.23  | 55   | 0.6930          | 0.5342   | 0.5251 |
| No log        | 4.62  | 60   | 0.6931          | 0.5417   | 0.5217 |
| No log        | 5.0   | 65   | 0.6931          | 0.5592   | 0.5482 |
| No log        | 5.38  | 70   | 0.6931          | 0.5667   | 0.5517 |
| No log        | 5.77  | 75   | 0.6931          | 0.5458   | 0.5362 |
| No log        | 6.15  | 80   | 0.6931          | 0.535    | 0.5311 |
| No log        | 6.54  | 85   | 0.6930          | 0.5433   | 0.5276 |
| No log        | 6.92  | 90   | 0.6931          | 0.5025   | 0.4731 |
| No log        | 7.31  | 95   | 0.6931          | 0.505    | 0.4715 |
| No log        | 7.69  | 100  | 0.6931          | 0.5017   | 0.4514 |
| No log        | 8.08  | 105  | 0.6931          | 0.5042   | 0.4831 |
| No log        | 8.46  | 110  | 0.6931          | 0.5058   | 0.4785 |
| No log        | 8.85  | 115  | 0.6931          | 0.5158   | 0.4872 |
| No log        | 9.23  | 120  | 0.6931          | 0.5158   | 0.4890 |
| No log        | 9.62  | 125  | 0.6931          | 0.5075   | 0.4829 |
| No log        | 10.0  | 130  | 0.6931          | 0.505    | 0.4780 |
| No log        | 10.38 | 135  | 0.6931          | 0.5      | 0.4709 |
| No log        | 10.77 | 140  | 0.6931          | 0.485    | 0.4579 |
| No log        | 11.15 | 145  | 0.6931          | 0.4858   | 0.4592 |
| No log        | 11.54 | 150  | 0.6931          | 0.485    | 0.4569 |
| No log        | 11.92 | 155  | 0.6931          | 0.4917   | 0.4611 |
| No log        | 12.31 | 160  | 0.6931          | 0.4908   | 0.4664 |
| No log        | 12.69 | 165  | 0.6931          | 0.4858   | 0.4602 |
| No log        | 13.08 | 170  | 0.6931          | 0.4983   | 0.4756 |
| No log        | 13.46 | 175  | 0.6931          | 0.4992   | 0.4788 |
| No log        | 13.85 | 180  | 0.6931          | 0.4942   | 0.4717 |
| No log        | 14.23 | 185  | 0.6931          | 0.4958   | 0.4735 |
| No log        | 14.62 | 190  | 0.6931          | 0.5017   | 0.48   |
| No log        | 15.0  | 195  | 0.6931          | 0.4942   | 0.4633 |
| No log        | 15.38 | 200  | 0.6931          | 0.4942   | 0.4527 |
| No log        | 15.77 | 205  | 0.6931          | 0.4925   | 0.4509 |
| No log        | 16.15 | 210  | 0.6931          | 0.495    | 0.4570 |
| No log        | 16.54 | 215  | 0.6931          | 0.4933   | 0.4581 |
| No log        | 16.92 | 220  | 0.6931          | 0.5      | 0.4671 |


### Framework versions

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