|
--- |
|
base_model: wav2vec2-pretrained-base-gumbelVQ |
|
tags: |
|
- automatic-speech-recognition |
|
- timit_asr |
|
- generated_from_trainer |
|
datasets: |
|
- timit_asr |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-base-gumbelVQ-timit-fine-tuned |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: TIMIT_ASR - NA |
|
type: timit_asr |
|
config: clean |
|
split: test |
|
args: 'Config: na, Training split: train, Eval split: test' |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.4901798635517883 |
|
--- |
|
|
|
<!-- 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-gumbelVQ-timit-fine-tuned |
|
|
|
This model is a fine-tuned version of [wav2vec2-pretrained-base-gumbelVQ](https://huggingface.co/wav2vec2-pretrained-base-gumbelVQ) on the TIMIT_ASR - NA dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7549 |
|
- Wer: 0.4902 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 1 |
|
- 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: 20.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 0.4628 | 10.0 | 1450 | 0.6779 | 0.5171 | |
|
| 0.3036 | 20.0 | 2900 | 0.7549 | 0.4902 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.36.2 |
|
- Pytorch 2.3.0.dev20231229+cu118 |
|
- Datasets 2.16.0 |
|
- Tokenizers 0.15.0 |
|
|
