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library_name: transformers
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: MSP
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
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: 1.2884
- Wer: 0.2160
- Cer: 0.1050
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 2.4417 | 0.05 | 500 | 1.5634 | 0.3213 | 0.1614 |
| 2.4653 | 0.1 | 1000 | 1.4770 | 0.2440 | 0.1209 |
| 2.3656 | 0.15 | 1500 | 1.4239 | 0.2407 | 0.1159 |
| 2.4607 | 0.2 | 2000 | 1.6669 | 0.2859 | 0.1395 |
| 2.2601 | 0.25 | 2500 | 1.3392 | 0.2444 | 0.1203 |
| 2.2054 | 0.3 | 3000 | 1.3330 | 0.2428 | 0.1188 |
| 2.0611 | 0.35 | 3500 | 1.8721 | 0.3652 | 0.1965 |
| 2.2652 | 0.4 | 4000 | 1.2884 | 0.2160 | 0.1050 |
| 2.1945 | 0.45 | 4500 | 2.0405 | 0.3451 | 0.1868 |
| 2.4363 | 0.5 | 5000 | 1.4916 | 0.2734 | 0.1337 |
| 2.1200 | 0.55 | 5500 | 1.4868 | 0.2515 | 0.1258 |
| 2.2227 | 0.6 | 6000 | 1.3656 | 0.2379 | 0.1165 |
| 2.0990 | 0.65 | 6500 | 1.4576 | 0.2552 | 0.1291 |
| 2.1397 | 0.7 | 7000 | 1.5793 | 0.2792 | 0.1428 |
| 2.1740 | 0.75 | 7500 | 1.4444 | 0.2380 | 0.1191 |
| 2.3435 | 0.8 | 8000 | 1.4126 | 0.2435 | 0.1231 |
| 2.0578 | 0.85 | 8500 | 1.3806 | 0.2347 | 0.1165 |
| 2.1130 | 0.9 | 9000 | 1.4284 | 0.2449 | 0.1226 |
| 2.1455 | 0.95 | 9500 | 1.4427 | 0.2475 | 0.1233 |
| 2.1259 | 1.0 | 10000 | 1.4531 | 0.2497 | 0.1246 |
### Framework versions
- Transformers 5.10.2
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
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