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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- librispeech_asr_dummy
metrics:
- wer
model-index:
- name: wav2vec2-base-librispeech
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: librispeech_asr_dummy
type: librispeech_asr_dummy
config: clean
split: None
args: clean
metrics:
- name: Wer
type: wer
value: 0.44274809160305345
---
<!-- 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. -->
# wav2vec2-base-librispeech
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the librispeech_asr_dummy dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8630
- Wer: 0.4427
## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 60
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0416 | 29.41 | 500 | 0.8917 | 0.4275 |
| 0.0419 | 58.82 | 1000 | 0.8630 | 0.4427 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|