---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-robust-ft-libri-960h
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: MSP-ASR
  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-ASR

This model is a fine-tuned version of [facebook/wav2vec2-large-robust-ft-libri-960h](https://huggingface.co/facebook/wav2vec2-large-robust-ft-libri-960h) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3481
- Wer: 0.2040

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 40000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 2.9991        | 0.025 | 1000  | 0.7600          | 0.4273 |
| 2.7153        | 0.05  | 2000  | 0.5967          | 0.3697 |
| 2.4461        | 0.075 | 3000  | 0.5058          | 0.3102 |
| 2.4391        | 0.1   | 4000  | 0.5428          | 0.2994 |
| 2.4508        | 0.125 | 5000  | 0.6064          | 0.3583 |
| 2.0697        | 0.15  | 6000  | 0.4450          | 0.2544 |
| 2.0818        | 0.175 | 7000  | 0.7904          | 0.3479 |
| 2.1906        | 0.2   | 8000  | 0.6347          | 0.3174 |
| 2.1315        | 0.225 | 9000  | 0.5940          | 0.3114 |
| 2.0303        | 0.25  | 10000 | 0.7855          | 0.3289 |
| 1.9732        | 0.275 | 11000 | 0.4407          | 0.2292 |
| 1.7688        | 0.3   | 12000 | 0.9236          | 0.3608 |
| 2.0256        | 0.325 | 13000 | 0.4565          | 0.2409 |
| 2.1277        | 0.35  | 14000 | 0.6548          | 0.3096 |
| 1.9222        | 0.375 | 15000 | 0.4132          | 0.2314 |
| 1.8986        | 0.4   | 16000 | 0.3661          | 0.2074 |
| 1.9326        | 0.425 | 17000 | 0.3481          | 0.2040 |
| 1.9936        | 0.45  | 18000 | 0.5246          | 0.2579 |
| 1.9033        | 0.475 | 19000 | 0.4698          | 0.2397 |
| 1.8331        | 0.5   | 20000 | 0.4469          | 0.2189 |
| 2.0719        | 0.525 | 21000 | 0.6117          | 0.2701 |
| 1.8486        | 0.55  | 22000 | 0.4878          | 0.2329 |
| 1.7071        | 0.575 | 23000 | 0.6653          | 0.2782 |
| 1.7644        | 0.6   | 24000 | 0.6700          | 0.2846 |
| 1.6879        | 0.625 | 25000 | 0.7342          | 0.2891 |
| 1.9840        | 0.65  | 26000 | 0.8277          | 0.3100 |
| 1.7513        | 0.675 | 27000 | 0.6867          | 0.2832 |
| 1.7917        | 0.7   | 28000 | 0.5828          | 0.2630 |
| 1.9621        | 0.725 | 29000 | 0.4499          | 0.2243 |
| 1.8372        | 0.75  | 30000 | 0.5036          | 0.2397 |
| 1.8334        | 0.775 | 31000 | 0.5540          | 0.2513 |
| 1.7985        | 0.8   | 32000 | 0.6490          | 0.2780 |
| 1.7205        | 0.825 | 33000 | 0.5828          | 0.2615 |
| 2.1699        | 0.85  | 34000 | 0.6067          | 0.2732 |
| 1.7843        | 0.875 | 35000 | 0.5375          | 0.2540 |
| 1.8201        | 0.9   | 36000 | 0.5541          | 0.2564 |
| 1.6863        | 0.925 | 37000 | 0.5362          | 0.2512 |
| 1.7110        | 0.95  | 38000 | 0.5339          | 0.2495 |
| 1.7379        | 0.975 | 39000 | 0.5395          | 0.2505 |
| 1.8971        | 1.0   | 40000 | 0.5416          | 0.2509 |


### Framework versions

- Transformers 5.10.2
- Pytorch 2.10.0+rocm7.2.4.git3d3aa833
- Datasets 4.0.0
- Tokenizers 0.22.2