---
library_name: transformers
license: apache-2.0
base_model: Asiif/mt5_hieroglyph
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mt5_hieroglyph
  results:
  - task:
      type: text2text-generation
      name: Text-to-Text Generation
    dataset:
      name: custom_hieroglyph_dataset
      type: custom
    metrics:
    - type: bleu
      value: 71.45810723232168
      name: BLEU
---

<!-- 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_hieroglyph

This model is a fine-tuned version of [Asiif/mt5_hieroglyph](https://huggingface.co/Asiif/mt5_hieroglyph) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3105
- Bleu: 71.4581
- Chrf: 77.3596

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.08
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Chrf    |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.077         | 10.0  | 6470  | 2.1542          | 70.7322 | 76.6222 |
| 0.0653        | 20.0  | 12940 | 2.3105          | 71.4581 | 77.3596 |
| 0.0593        | 30.0  | 19410 | 2.4402          | 71.1786 | 77.0790 |
| 0.097         | 40.0  | 25880 | 2.0266          | 70.9717 | 77.2137 |
| 0.1197        | 50.0  | 32350 | 1.7680          | 71.1443 | 77.4270 |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.9.0+cu126
- Datasets 3.1.0
- Tokenizers 0.22.2