---
license: mit
base_model: facebook/xlm-v-base
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
- f1
model-index:
- name: scenario-TCR_data-cl-massive_all_1_1
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: massive
      type: massive
      config: all_1.1
      split: validation
      args: all_1.1
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7991474012133136
    - name: F1
      type: f1
      value: 0.754097240958744
---

<!-- 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_data-cl-massive_all_1_1

This model is a fine-tuned version of [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-base) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2577
- Accuracy: 0.7991
- F1: 0.7541

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.585         | 0.56  | 5000  | 0.9018          | 0.7809   | 0.7207 |
| 0.344         | 1.11  | 10000 | 0.9305          | 0.7891   | 0.7376 |
| 0.2938        | 1.67  | 15000 | 0.9186          | 0.7905   | 0.7357 |
| 0.1892        | 2.22  | 20000 | 1.0155          | 0.7918   | 0.7414 |
| 0.1781        | 2.78  | 25000 | 1.0659          | 0.7916   | 0.7479 |
| 0.1064        | 3.33  | 30000 | 1.1471          | 0.7987   | 0.7540 |
| 0.1014        | 3.89  | 35000 | 1.1831          | 0.7983   | 0.7497 |
| 0.0731        | 4.45  | 40000 | 1.2577          | 0.7991   | 0.7541 |


### Framework versions

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