---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-300m
tags:
- automatic-speech-recognition
- libri10h
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-300m-librispeech-test
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-300m-librispeech-test

This model is a fine-tuned version of [facebook/mms-300m](https://huggingface.co/facebook/mms-300m) on the LIBRI10H - ENG dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8825
- Wer: 1.0

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 2.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:---:|
| 6.037         | 0.2899 | 100  | 2.9196          | 1.0 |
| 2.8559        | 0.5797 | 200  | 2.8880          | 1.0 |
| 2.8547        | 0.8696 | 300  | 2.8900          | 1.0 |
| 2.8418        | 1.1594 | 400  | 2.9082          | 1.0 |
| 2.8436        | 1.4493 | 500  | 2.8775          | 1.0 |
| 2.8373        | 1.7391 | 600  | 2.8821          | 1.0 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0