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---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: MSP-Visual
  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. -->

# MSP-Visual

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3334
- Wer: 0.6493
- Cer: 0.3725

## 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: 32
- eval_batch_size: 32
- seed: 42
- 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_steps: 1000.0
- training_steps: 20000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 2.5771        | 0.05  | 1000  | 2.3988          | 0.9791 | 0.6114 |
| 2.0987        | 0.1   | 2000  | 1.7770          | 0.8288 | 0.4786 |
| 1.9764        | 0.15  | 3000  | 1.6459          | 0.7827 | 0.4485 |
| 1.9493        | 0.2   | 4000  | 1.6139          | 0.7614 | 0.4388 |
| 1.9069        | 0.25  | 5000  | 1.5498          | 0.7351 | 0.4191 |
| 1.9144        | 0.3   | 6000  | 1.5212          | 0.7212 | 0.4142 |
| 1.8289        | 0.35  | 7000  | 1.4857          | 0.7139 | 0.4063 |
| 1.8845        | 0.4   | 8000  | 1.4832          | 0.6958 | 0.3979 |
| 1.7763        | 0.45  | 9000  | 1.4466          | 0.6938 | 0.3946 |
| 1.9370        | 0.5   | 10000 | 1.4235          | 0.6825 | 0.3916 |
| 1.7678        | 0.55  | 11000 | 1.4164          | 0.6784 | 0.3857 |
| 1.8403        | 0.6   | 12000 | 1.3981          | 0.6696 | 0.3868 |
| 1.6723        | 0.65  | 13000 | 1.3849          | 0.6631 | 0.3769 |
| 1.7040        | 0.7   | 14000 | 1.3884          | 0.6579 | 0.3763 |
| 1.5821        | 0.75  | 15000 | 1.3599          | 0.6588 | 0.3756 |
| 1.5721        | 0.8   | 16000 | 1.3480          | 0.6519 | 0.3728 |
| 1.6635        | 0.85  | 17000 | 1.3432          | 0.6527 | 0.3732 |
| 1.6557        | 0.9   | 18000 | 1.3501          | 0.6525 | 0.3748 |
| 1.7992        | 0.95  | 19000 | 1.3334          | 0.6493 | 0.3725 |
| 1.7090        | 1.0   | 20000 | 1.3328          | 0.6499 | 0.3724 |


### Framework versions

- Transformers 5.10.2
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2