---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: MSP-Fusion
  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-Fusion

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: 0.4092
- Wer: 0.2350
- Cer: 0.1167

## 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: 0.0002
- 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: 500
- training_steps: 10000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 0.9948        | 0.05  | 500   | 0.4387          | 0.2571 | 0.1277 |
| 1.1610        | 0.1   | 1000  | 0.4477          | 0.2550 | 0.1237 |
| 0.9327        | 0.15  | 1500  | 0.4221          | 0.2414 | 0.1188 |
| 1.0052        | 0.2   | 2000  | 0.4231          | 0.2476 | 0.1231 |
| 0.9512        | 0.25  | 2500  | 0.4339          | 0.2556 | 0.1288 |
| 0.9423        | 0.3   | 3000  | 0.4389          | 0.2580 | 0.1278 |
| 0.8131        | 0.35  | 3500  | 0.4282          | 0.2489 | 0.1247 |
| 0.9237        | 0.4   | 4000  | 0.4336          | 0.2464 | 0.1219 |
| 0.9842        | 0.45  | 4500  | 0.4305          | 0.2559 | 0.1290 |
| 1.0400        | 0.5   | 5000  | 0.4241          | 0.2426 | 0.1199 |
| 0.9045        | 0.55  | 5500  | 0.4265          | 0.2449 | 0.1215 |
| 0.9655        | 0.6   | 6000  | 0.4266          | 0.2430 | 0.1204 |
| 0.8683        | 0.65  | 6500  | 0.4139          | 0.2379 | 0.1178 |
| 0.8457        | 0.7   | 7000  | 0.4124          | 0.2372 | 0.1178 |
| 0.9675        | 0.75  | 7500  | 0.4133          | 0.2369 | 0.1189 |
| 0.9740        | 0.8   | 8000  | 0.4178          | 0.2406 | 0.1208 |
| 0.9536        | 0.85  | 8500  | 0.4092          | 0.2350 | 0.1167 |
| 0.9858        | 0.9   | 9000  | 0.4144          | 0.2378 | 0.1184 |
| 0.9754        | 0.95  | 9500  | 0.4113          | 0.2366 | 0.1174 |
| 0.9603        | 1.0   | 10000 | 0.4126          | 0.2373 | 0.1177 |


### Framework versions

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