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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
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