---
library_name: transformers
license: apache-2.0
base_model: google/mt5-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: mt5_base_lr3e-05_bs4_ep3
  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. -->

# mt5_base_lr3e-05_bs4_ep3

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4883
- Precision: 0.5950
- Recall: 0.2925
- F1: 0.3922
- Accuracy: 0.7879

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 1.1875        | 1.0   | 860  | 0.5606          | 0.6255    | 0.0959 | 0.1662 | 0.7750   |
| 0.6539        | 2.0   | 1720 | 0.4923          | 0.5507    | 0.3642 | 0.4384 | 0.7817   |
| 0.5954        | 3.0   | 2580 | 0.4883          | 0.5950    | 0.2925 | 0.3922 | 0.7879   |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1