---
license: mit
base_model: facebook/xlm-v-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: scenario-TCR-XLMV-XCOPA-6_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-6_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: 0.535
- F1: 0.5114

## 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: 341241
- 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    | 0.6931          | 0.5317   | 0.4955 |
| No log        | 0.77  | 10   | 0.6931          | 0.4917   | 0.4592 |
| No log        | 1.15  | 15   | 0.6931          | 0.535    | 0.5053 |
| No log        | 1.54  | 20   | 0.6932          | 0.4867   | 0.4643 |
| No log        | 1.92  | 25   | 0.6931          | 0.5217   | 0.5017 |
| No log        | 2.31  | 30   | 0.6935          | 0.4967   | 0.4655 |
| No log        | 2.69  | 35   | 0.6930          | 0.5033   | 0.4726 |
| No log        | 3.08  | 40   | 0.6932          | 0.49     | 0.4622 |
| No log        | 3.46  | 45   | 0.6931          | 0.5225   | 0.4833 |
| No log        | 3.85  | 50   | 0.6931          | 0.4983   | 0.4738 |
| No log        | 4.23  | 55   | 0.6931          | 0.5217   | 0.4974 |
| No log        | 4.62  | 60   | 0.6931          | 0.5475   | 0.5216 |
| No log        | 5.0   | 65   | 0.6931          | 0.5467   | 0.5169 |
| No log        | 5.38  | 70   | 0.6931          | 0.5425   | 0.5129 |
| No log        | 5.77  | 75   | 0.6931          | 0.5433   | 0.5133 |
| No log        | 6.15  | 80   | 0.6931          | 0.5417   | 0.5107 |
| No log        | 6.54  | 85   | 0.6931          | 0.5458   | 0.5121 |
| No log        | 6.92  | 90   | 0.6931          | 0.5417   | 0.5098 |
| No log        | 7.31  | 95   | 0.6931          | 0.5483   | 0.5152 |
| No log        | 7.69  | 100  | 0.6931          | 0.5525   | 0.5201 |
| No log        | 8.08  | 105  | 0.6931          | 0.5342   | 0.5092 |
| No log        | 8.46  | 110  | 0.6931          | 0.5158   | 0.4943 |
| No log        | 8.85  | 115  | 0.6931          | 0.5483   | 0.5178 |
| No log        | 9.23  | 120  | 0.6931          | 0.505    | 0.4715 |
| No log        | 9.62  | 125  | 0.6931          | 0.4825   | 0.4440 |
| No log        | 10.0  | 130  | 0.6931          | 0.4767   | 0.4353 |
| No log        | 10.38 | 135  | 0.6931          | 0.4642   | 0.4315 |
| No log        | 10.77 | 140  | 0.6931          | 0.5458   | 0.5156 |
| No log        | 11.15 | 145  | 0.6931          | 0.54     | 0.5098 |
| No log        | 11.54 | 150  | 0.6931          | 0.5458   | 0.5164 |
| No log        | 11.92 | 155  | 0.6931          | 0.5442   | 0.5172 |
| No log        | 12.31 | 160  | 0.6931          | 0.5375   | 0.5119 |
| No log        | 12.69 | 165  | 0.6932          | 0.4667   | 0.4386 |
| No log        | 13.08 | 170  | 0.6931          | 0.5383   | 0.5157 |
| No log        | 13.46 | 175  | 0.6931          | 0.5375   | 0.5136 |
| No log        | 13.85 | 180  | 0.6931          | 0.5392   | 0.5162 |
| No log        | 14.23 | 185  | 0.6931          | 0.5392   | 0.5179 |
| No log        | 14.62 | 190  | 0.6931          | 0.5417   | 0.5192 |
| No log        | 15.0  | 195  | 0.6931          | 0.5392   | 0.5162 |
| No log        | 15.38 | 200  | 0.6931          | 0.5383   | 0.5149 |
| No log        | 15.77 | 205  | 0.6931          | 0.535    | 0.5122 |
| No log        | 16.15 | 210  | 0.6931          | 0.535    | 0.5114 |


### Framework versions

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