---
license: mit
base_model: facebook/xlm-v-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-TCR-XLMV-XCOPA-3_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-3_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: 0.4625
- F1: 0.4277

## 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: 48
- 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          | 0.4725   | 0.4472 |
| No log        | 0.77  | 10   | 0.6932          | 0.4892   | 0.4656 |
| No log        | 1.15  | 15   | 0.6932          | 0.4867   | 0.45   |
| No log        | 1.54  | 20   | 0.6932          | 0.49     | 0.4584 |
| No log        | 1.92  | 25   | 0.6931          | 0.51     | 0.4722 |
| No log        | 2.31  | 30   | 0.6931          | 0.5042   | 0.4730 |
| No log        | 2.69  | 35   | 0.6932          | 0.4825   | 0.4576 |
| No log        | 3.08  | 40   | 0.6931          | 0.4767   | 0.4520 |
| No log        | 3.46  | 45   | 0.6931          | 0.4842   | 0.4556 |
| No log        | 3.85  | 50   | 0.6931          | 0.4883   | 0.4508 |
| No log        | 4.23  | 55   | 0.6931          | 0.5392   | 0.5145 |
| No log        | 4.62  | 60   | 0.6931          | 0.5508   | 0.5183 |
| No log        | 5.0   | 65   | 0.6931          | 0.5392   | 0.5076 |
| No log        | 5.38  | 70   | 0.6931          | 0.5567   | 0.5325 |
| No log        | 5.77  | 75   | 0.6931          | 0.5642   | 0.5368 |
| No log        | 6.15  | 80   | 0.6931          | 0.4483   | 0.4173 |
| No log        | 6.54  | 85   | 0.6931          | 0.4358   | 0.4025 |
| No log        | 6.92  | 90   | 0.6931          | 0.4492   | 0.4257 |
| No log        | 7.31  | 95   | 0.6931          | 0.4442   | 0.4185 |
| No log        | 7.69  | 100  | 0.6931          | 0.4492   | 0.4207 |
| No log        | 8.08  | 105  | 0.6931          | 0.4575   | 0.4294 |
| No log        | 8.46  | 110  | 0.6931          | 0.4592   | 0.4322 |
| No log        | 8.85  | 115  | 0.6931          | 0.4583   | 0.4268 |
| No log        | 9.23  | 120  | 0.6931          | 0.4567   | 0.4240 |
| No log        | 9.62  | 125  | 0.6931          | 0.465    | 0.4309 |
| No log        | 10.0  | 130  | 0.6931          | 0.5608   | 0.5239 |
| No log        | 10.38 | 135  | 0.6931          | 0.5525   | 0.5244 |
| No log        | 10.77 | 140  | 0.6931          | 0.5542   | 0.5253 |
| No log        | 11.15 | 145  | 0.6931          | 0.5567   | 0.5284 |
| No log        | 11.54 | 150  | 0.6931          | 0.5517   | 0.5247 |
| No log        | 11.92 | 155  | 0.6931          | 0.5567   | 0.5325 |
| No log        | 12.31 | 160  | 0.6931          | 0.5483   | 0.5271 |
| No log        | 12.69 | 165  | 0.6931          | 0.5183   | 0.5009 |
| No log        | 13.08 | 170  | 0.6931          | 0.5125   | 0.4891 |
| No log        | 13.46 | 175  | 0.6931          | 0.4917   | 0.4696 |
| No log        | 13.85 | 180  | 0.6931          | 0.4683   | 0.4462 |
| No log        | 14.23 | 185  | 0.6931          | 0.4758   | 0.4507 |
| No log        | 14.62 | 190  | 0.6931          | 0.515    | 0.4913 |
| No log        | 15.0  | 195  | 0.6931          | 0.5242   | 0.5048 |
| No log        | 15.38 | 200  | 0.6931          | 0.5208   | 0.4996 |
| No log        | 15.77 | 205  | 0.6931          | 0.4567   | 0.4389 |
| No log        | 16.15 | 210  | 0.6931          | 0.4492   | 0.4145 |
| No log        | 16.54 | 215  | 0.6931          | 0.465    | 0.4309 |
| No log        | 16.92 | 220  | 0.6931          | 0.4633   | 0.4270 |
| No log        | 17.31 | 225  | 0.6931          | 0.4625   | 0.4277 |


### Framework versions

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