|
--- |
|
base_model: lnxdx/20_2000_1e-5_hp-mehrdad |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: B4_1000_1e-5_hp-myself-2 |
|
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. --> |
|
|
|
# B4_1000_1e-5_hp-myself-2 |
|
|
|
This model is a fine-tuned version of [lnxdx/20_2000_1e-5_hp-mehrdad](https://huggingface.co/lnxdx/20_2000_1e-5_hp-mehrdad) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss on ShEMO train set: 0.7516 |
|
- Loss on ShEMO dev set: 0.6705 |
|
- WER on ShEMO train set: 28.02 |
|
- WER on ShEMO dev set: 31.16 |
|
- WER on Common Voice 13 test set: 19.34 |
|
|
|
## 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: 500 |
|
- training_steps: 1000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 0.8083 | 0.62 | 100 | 0.6766 | 0.3271 | |
|
| 0.8414 | 1.25 | 200 | 0.6774 | 0.3259 | |
|
| 0.8465 | 1.88 | 300 | 0.6686 | 0.3262 | |
|
| 0.7819 | 2.5 | 400 | 0.6749 | 0.3207 | |
|
| 0.7905 | 3.12 | 500 | 0.6848 | 0.3178 | |
|
| 0.8078 | 3.75 | 600 | 0.6571 | 0.3245 | |
|
| 0.7771 | 4.38 | 700 | 0.6683 | 0.3145 | |
|
| 0.7786 | 5.0 | 800 | 0.6688 | 0.3137 | |
|
| 0.7656 | 5.62 | 900 | 0.6703 | 0.3134 | |
|
| 0.7516 | 6.25 | 1000 | 0.6706 | 0.3131 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|