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# scenario-TCR-data-cl-massive-all_1.1

This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4731
- Accuracy: 0.7589
- F1: 0.7085

## 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     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 0.538         | 0.56  | 5000  | 1.0424          | 0.7443   | 0.6838 |
| 0.3231        | 1.11  | 10000 | 1.0765          | 0.7546   | 0.6892 |
| 0.2903        | 1.67  | 15000 | 1.0955          | 0.7515   | 0.6948 |
| 0.1815        | 2.22  | 20000 | 1.2437          | 0.7543   | 0.7015 |
| 0.1726        | 2.78  | 25000 | 1.2138          | 0.7552   | 0.7043 |
| 0.1128        | 3.33  | 30000 | 1.3161          | 0.7609   | 0.7161 |
| 0.1082        | 3.89  | 35000 | 1.3587          | 0.7586   | 0.7131 |
| 0.0635        | 4.45  | 40000 | 1.4731          | 0.7589   | 0.7085 |


### 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": "xlm-roberta-base", "model-index": [{"name": "scenario-TCR-data-cl-massive-all_1.1", "results": [{"task": {"type": "text-classification", "name": "Text Classification"}, "dataset": {"name": "massive", "type": "massive", "config": "all_1.1", "split": "validation", "args": "all_1.1"}, "metrics": [{"type": "accuracy", "value": 0.7589040097648067, "name": "Accuracy"}, {"type": "f1", "value": 0.7085443658514438, "name": "F1"}]}]}]}
transformers pytorch xlm-roberta text-classification generated_from_trainer dataset:massive base_model:xlm-roberta-base license:mit model-index autotrain_compatible endpoints_compatible region:us