---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b
tags:
- generated_from_trainer
model-index:
- name: mms-1b-gui
  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. -->

# mms-1b-gui

This model is a fine-tuned version of [facebook/mms-1b](https://huggingface.co/facebook/mms-1b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1145
- Cer: 0.2776

## 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: 0.0003
- 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: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 7.8773        | 0.4329 | 100  | 1.5370          | 0.4601 |
| 2.6159        | 0.8658 | 200  | 1.0908          | 0.3136 |
| 2.2120        | 1.2987 | 300  | 0.8812          | 0.2603 |
| 1.9035        | 1.7316 | 400  | 0.8390          | 0.2335 |
| 1.7596        | 2.1645 | 500  | 0.7883          | 0.2456 |
| 1.4815        | 2.5974 | 600  | 0.7664          | 0.2175 |
| 1.5555        | 3.0303 | 700  | 0.7294          | 0.2231 |
| 1.2112        | 3.4632 | 800  | 0.7387          | 0.2377 |
| 1.2092        | 3.8961 | 900  | 0.6927          | 0.2201 |
| 1.1119        | 4.3290 | 1000 | 0.6847          | 0.2048 |
| 1.0152        | 4.7619 | 1100 | 0.6740          | 0.1889 |
| 1.0220        | 5.1948 | 1200 | 0.6773          | 0.2003 |
| 1.2641        | 5.6277 | 1300 | 0.9480          | 0.2511 |
| 2.1819        | 6.0606 | 1400 | 1.4692          | 0.3210 |
| 2.7651        | 6.4935 | 1500 | 1.4108          | 0.4450 |
| 2.4741        | 6.9264 | 1600 | 1.2238          | 0.3591 |
| 3.6614        | 7.3593 | 1700 | 1.1802          | 0.3484 |
| 2.1207        | 7.7922 | 1800 | 1.1016          | 0.3315 |
| 2.0560        | 8.2251 | 1900 | 1.0702          | 0.3137 |
| 2.0227        | 8.6580 | 2000 | 1.1102          | 0.2817 |
| 2.0418        | 9.0909 | 2100 | 1.1127          | 0.2782 |
| 2.0239        | 9.5238 | 2200 | 1.1074          | 0.2811 |
| 2.0523        | 9.9567 | 2300 | 1.1145          | 0.2776 |


### Framework versions

- Transformers 5.1.0
- Pytorch 2.9.1+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2