|
|
--- |
|
|
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 |
|
|
|
