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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-lv60
tags:
- automatic-speech-recognition
- librispeech_asr
- generated_from_trainer
datasets:
- librispeech_asr
metrics:
- wer
model-index:
- name: wav2vec2-librispeech-demo
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: LIBRISPEECH_ASR - CLEAN
type: librispeech_asr
config: clean
split: test
args: 'Config: clean, Training split: test, Eval split: test'
metrics:
- name: Wer
type: wer
value: 1.0225474683544304
---
<!-- 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-librispeech-demo
This model is a fine-tuned version of [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) on the LIBRISPEECH_ASR - CLEAN dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0030
- Wer: 1.0225
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| No log | 0.6329 | 100 | 3.9409 | 1.0 |
| No log | 1.2658 | 200 | 3.0441 | 1.0 |
| No log | 1.8987 | 300 | 2.9165 | 1.0 |
| No log | 2.5316 | 400 | 1.4925 | 1.9968 |
| 3.7012 | 3.1646 | 500 | 0.3010 | 1.9446 |
| 3.7012 | 3.7975 | 600 | 0.1713 | 1.8259 |
| 3.7012 | 4.4304 | 700 | 0.0990 | 1.6163 |
| 3.7012 | 5.0633 | 800 | 0.0692 | 1.5439 |
| 3.7012 | 5.6962 | 900 | 0.0463 | 1.4233 |
| 0.1686 | 6.3291 | 1000 | 0.0389 | 1.3469 |
| 0.1686 | 6.9620 | 1100 | 0.0290 | 1.3101 |
| 0.1686 | 7.5949 | 1200 | 0.0204 | 1.1994 |
| 0.1686 | 8.2278 | 1300 | 0.0161 | 1.1839 |
| 0.1686 | 8.8608 | 1400 | 0.0143 | 1.1499 |
| 0.0553 | 9.4937 | 1500 | 0.0110 | 1.1460 |
| 0.0553 | 10.1266 | 1600 | 0.0082 | 1.0953 |
| 0.0553 | 10.7595 | 1700 | 0.0088 | 1.1119 |
| 0.0553 | 11.3924 | 1800 | 0.0059 | 1.0574 |
| 0.0553 | 12.0253 | 1900 | 0.0054 | 1.0510 |
| 0.0295 | 12.6582 | 2000 | 0.0042 | 1.0356 |
| 0.0295 | 13.2911 | 2100 | 0.0039 | 1.0360 |
| 0.0295 | 13.9241 | 2200 | 0.0033 | 1.0269 |
| 0.0295 | 14.5570 | 2300 | 0.0031 | 1.0237 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.5.1
- Datasets 2.21.0
- Tokenizers 0.19.1
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