---
library_name: transformers
license: mit
base_model: facebook/m2m100_1.2B
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: m2m100_1.2B-ft-en-to-cy
  results: []
datasets:
- techiaith/llyw-cymru-en-cy-ogl
- mgrbyte/bydtermcymru-tm-en-cy
- mgrbyte/cardiff-university-tm-en-cy
- mgrbyte/cwm-taf-morgannwg-university-health-board-tm-en-cy
language:
- cy
- en
pipeline_tag: translation
---

<!-- 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. -->

# m2m100_1.2B-ft-en-to-cy

This model is a fine-tuned version of [facebook/m2m100_1.2B](https://huggingface.co/facebook/m2m100_1.2B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5864
- Bleu: 54.8016
- Gen Len: 33.9191

## 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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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: 6000
- training_steps: 30000

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:------:|:-----:|:---------------:|:-------:|:-------:|
| 2.3252        | 0.0166 | 2000  | 1.9613          | 21.0612 | 35.9022 |
| 1.5651        | 0.0332 | 4000  | 1.2919          | 34.3962 | 34.8431 |
| 1.1755        | 0.0499 | 6000  | 0.9977          | 42.2725 | 34.4593 |
| 0.9801        | 0.0665 | 8000  | 0.8545          | 46.4396 | 33.9573 |
| 0.8697        | 0.0831 | 10000 | 0.7763          | 48.9327 | 34.0146 |
| 0.813         | 0.0997 | 12000 | 0.7224          | 50.2154 | 33.8613 |
| 0.779         | 0.1164 | 14000 | 0.6911          | 51.4013 | 33.9477 |
| 0.7436        | 0.1330 | 16000 | 0.6648          | 52.2204 | 33.9345 |
| 0.7224        | 0.1496 | 18000 | 0.6437          | 52.9165 | 33.9964 |
| 0.7034        | 0.1662 | 20000 | 0.6279          | 53.6142 | 33.9663 |
| 0.6783        | 0.1829 | 22000 | 0.6134          | 53.7386 | 33.9527 |
| 0.6765        | 0.1995 | 24000 | 0.6029          | 54.4546 | 33.955  |
| 0.656         | 0.2161 | 26000 | 0.5941          | 54.5817 | 33.9145 |
| 0.6522        | 0.2327 | 28000 | 0.5884          | 54.728  | 33.9163 |
| 0.6562        | 0.2494 | 30000 | 0.5864          | 54.8016 | 33.9191 |


### Framework versions

- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1