|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: my_awesome_asr_mind_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. --> |
|
|
|
# my_awesome_asr_mind_model |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.8925 |
|
- Wer: 0.4558 |
|
|
|
## 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: 4 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 8 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- training_steps: 2000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 4.5119 | 1.77 | 100 | 4.1083 | 1.0 | |
|
| 3.287 | 3.54 | 200 | 3.2437 | 1.0 | |
|
| 3.1513 | 5.31 | 300 | 3.1230 | 1.0 | |
|
| 3.0487 | 7.08 | 400 | 3.0786 | 1.0 | |
|
| 3.0241 | 8.85 | 500 | 3.0934 | 1.0 | |
|
| 2.9968 | 10.62 | 600 | 2.9948 | 1.0 | |
|
| 2.9601 | 12.39 | 700 | 2.9549 | 1.0 | |
|
| 2.9061 | 14.16 | 800 | 2.8990 | 1.0 | |
|
| 2.3543 | 15.93 | 900 | 2.2582 | 0.9272 | |
|
| 1.3794 | 17.7 | 1000 | 1.7532 | 0.8179 | |
|
| 0.8947 | 19.47 | 1100 | 1.2148 | 0.6710 | |
|
| 0.5989 | 21.24 | 1200 | 1.3229 | 0.5579 | |
|
| 0.5861 | 23.01 | 1300 | 1.4233 | 0.5267 | |
|
| 0.4311 | 24.78 | 1400 | 1.5458 | 0.5104 | |
|
| 0.3286 | 26.55 | 1500 | 1.6509 | 0.5039 | |
|
| 0.2765 | 28.32 | 1600 | 1.6818 | 0.4948 | |
|
| 0.2541 | 30.09 | 1700 | 1.7650 | 0.4629 | |
|
| 0.2151 | 31.86 | 1800 | 1.7185 | 0.4460 | |
|
| 0.1959 | 33.63 | 1900 | 1.9164 | 0.4577 | |
|
| 0.1909 | 35.4 | 2000 | 1.8925 | 0.4558 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.1 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.1 |
|
|
