|
--- |
|
language: |
|
- tr |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-large-xlsr-53 |
|
tags: |
|
- automatic-speech-recognition |
|
- common_voice |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-common_voice-tr-demo |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: COMMON_VOICE - TR |
|
type: common_voice |
|
config: tr |
|
split: test |
|
args: 'Config: tr, Training split: train+validation, Eval split: test' |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.3428658972525789 |
|
--- |
|
|
|
<!-- 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-common_voice-tr-demo |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the COMMON_VOICE - TR dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3709 |
|
- Wer: 0.3429 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 32 |
|
- 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 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| No log | 0.92 | 100 | 3.5988 | 1.0 | |
|
| No log | 1.83 | 200 | 3.0083 | 0.9999 | |
|
| No log | 2.75 | 300 | 0.8642 | 0.7579 | |
|
| No log | 3.67 | 400 | 0.5713 | 0.6203 | |
|
| 3.14 | 4.59 | 500 | 0.4795 | 0.5338 | |
|
| 3.14 | 5.5 | 600 | 0.4441 | 0.4912 | |
|
| 3.14 | 6.42 | 700 | 0.4241 | 0.4521 | |
|
| 3.14 | 7.34 | 800 | 0.4326 | 0.4611 | |
|
| 3.14 | 8.26 | 900 | 0.3913 | 0.4212 | |
|
| 0.2183 | 9.17 | 1000 | 0.4036 | 0.3973 | |
|
| 0.2183 | 10.09 | 1100 | 0.4035 | 0.3959 | |
|
| 0.2183 | 11.01 | 1200 | 0.3807 | 0.3790 | |
|
| 0.2183 | 11.93 | 1300 | 0.3750 | 0.3650 | |
|
| 0.2183 | 12.84 | 1400 | 0.3822 | 0.3573 | |
|
| 0.1011 | 13.76 | 1500 | 0.3747 | 0.3510 | |
|
| 0.1011 | 14.68 | 1600 | 0.3714 | 0.3454 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.32.0.dev0 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.14.0 |
|
- Tokenizers 0.13.3 |
|
|