|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
base_model: facebook/wav2vec2-base |
|
datasets: |
|
- transcribed_calls |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-base-wonders-phonemes |
|
results: |
|
- task: |
|
type: automatic-speech-recognition |
|
name: Automatic Speech Recognition |
|
dataset: |
|
name: transcribed_calls |
|
type: transcribed_calls |
|
config: default |
|
split: None |
|
args: default |
|
metrics: |
|
- type: wer |
|
value: 1.0 |
|
name: Wer |
|
--- |
|
|
|
<!-- 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-wonders-phonemes |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the transcribed_calls dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.9444 |
|
- 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: 0.0001 |
|
- train_batch_size: 2 |
|
- eval_batch_size: 2 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 4 |
|
- total_train_batch_size: 8 |
|
- total_eval_batch_size: 8 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 30 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:---:| |
|
| 3.6803 | 3.17 | 200 | 4.2914 | 1.0 | |
|
| 3.5239 | 4.76 | 300 | 4.0735 | 1.0 | |
|
| 3.449 | 6.35 | 400 | 3.9754 | 1.0 | |
|
| 3.9913 | 7.94 | 500 | 3.9428 | 1.0 | |
|
| 3.3992 | 9.52 | 600 | 3.9585 | 1.0 | |
|
| 3.3712 | 11.11 | 700 | 3.9996 | 1.0 | |
|
| 3.3716 | 12.7 | 800 | 3.9949 | 1.0 | |
|
| 3.9369 | 14.29 | 900 | 3.9352 | 1.0 | |
|
| 3.3867 | 15.87 | 1000 | 3.9327 | 1.0 | |
|
| 3.3602 | 17.46 | 1100 | 3.9940 | 1.0 | |
|
| 3.4101 | 19.05 | 1200 | 3.9470 | 1.0 | |
|
| 3.3484 | 20.63 | 1300 | 3.9482 | 1.0 | |
|
| 4.4074 | 22.22 | 1400 | 3.9364 | 1.0 | |
|
| 3.9909 | 23.81 | 1500 | 3.9681 | 1.0 | |
|
| 3.3762 | 25.4 | 1600 | 3.9738 | 1.0 | |
|
| 3.357 | 26.98 | 1700 | 3.9504 | 1.0 | |
|
| 3.3729 | 28.57 | 1800 | 3.9444 | 1.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.39.1 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
