|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base-960h |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: model_sh_intit_model |
|
results: [] |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# model_sh_intit_model |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.4880 |
|
- Wer: 0.3617 |
|
- Cer: 0.9396 |
|
|
|
## 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: 1e-05 |
|
- 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: 100 |
|
- training_steps: 1000 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
|
| 0.9874 | 20.0 | 100 | 1.6657 | 0.5234 | 0.9457 | |
|
| 0.5576 | 40.0 | 200 | 1.0859 | 0.4426 | 0.9422 | |
|
| 0.399 | 60.0 | 300 | 1.2627 | 0.3957 | 0.9406 | |
|
| 0.2509 | 80.0 | 400 | 1.3391 | 0.3830 | 0.9405 | |
|
| 0.2643 | 100.0 | 500 | 1.4182 | 0.3787 | 0.9401 | |
|
| 0.1931 | 120.0 | 600 | 1.3800 | 0.3915 | 0.9403 | |
|
| 0.1553 | 140.0 | 700 | 1.4751 | 0.3957 | 0.9402 | |
|
| 0.1679 | 160.0 | 800 | 1.4633 | 0.3660 | 0.9397 | |
|
| 0.1642 | 180.0 | 900 | 1.5003 | 0.3617 | 0.9397 | |
|
| 0.1286 | 200.0 | 1000 | 1.4880 | 0.3617 | 0.9396 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.1 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.7 |
|
- Tokenizers 0.14.1 |
|
|
