|
--- |
|
base_model: nadsoft/Hamsa-large-v0.1-beta |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: hamsa-pretrained |
|
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. --> |
|
|
|
# hamsa-pretrained |
|
|
|
This model is a fine-tuned version of [nadsoft/Hamsa-large-v0.1-beta](https://huggingface.co/nadsoft/Hamsa-large-v0.1-beta) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4344 |
|
- Wer: 29.2057 |
|
|
|
## 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: 0.00025 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 500 |
|
- training_steps: 35000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:| |
|
| 1.895 | 0.01 | 1000 | 1.8765 | 86.7012 | |
|
| 1.6569 | 0.01 | 2000 | 1.5809 | 84.0907 | |
|
| 1.3312 | 0.02 | 3000 | 1.3458 | 75.7090 | |
|
| 1.2369 | 0.02 | 4000 | 1.2389 | 73.1365 | |
|
| 1.1518 | 0.03 | 5000 | 1.1097 | 66.8170 | |
|
| 1.0135 | 0.03 | 6000 | 1.0616 | 65.1843 | |
|
| 1.0965 | 0.04 | 7000 | 1.0084 | 65.8582 | |
|
| 0.867 | 0.04 | 8000 | 0.9305 | 57.6093 | |
|
| 0.9425 | 0.05 | 9000 | 0.8907 | 55.4854 | |
|
| 0.9501 | 0.05 | 10000 | 0.8393 | 54.0212 | |
|
| 0.8602 | 0.06 | 11000 | 0.8096 | 53.4968 | |
|
| 0.7596 | 0.06 | 12000 | 0.7761 | 51.9305 | |
|
| 0.7334 | 0.07 | 13000 | 0.7694 | 49.4411 | |
|
| 0.708 | 0.07 | 14000 | 0.7336 | 47.0040 | |
|
| 0.7112 | 0.08 | 15000 | 0.7149 | 47.5783 | |
|
| 0.6989 | 0.08 | 16000 | 0.6713 | 44.2986 | |
|
| 0.7025 | 0.09 | 17000 | 0.6639 | 43.7481 | |
|
| 0.6127 | 0.09 | 18000 | 0.6477 | 42.9127 | |
|
| 0.6342 | 0.1 | 19000 | 0.6298 | 42.6826 | |
|
| 0.6174 | 0.1 | 20000 | 0.6080 | 40.1172 | |
|
| 0.5551 | 0.11 | 21000 | 0.5896 | 39.0398 | |
|
| 0.5353 | 0.11 | 22000 | 0.5753 | 39.1253 | |
|
| 0.5528 | 0.12 | 23000 | 0.5588 | 40.2881 | |
|
| 0.5423 | 0.12 | 24000 | 0.5445 | 35.6606 | |
|
| 0.5069 | 0.13 | 25000 | 0.5304 | 35.9358 | |
|
| 0.4356 | 0.13 | 26000 | 0.5187 | 34.4930 | |
|
| 0.5111 | 0.14 | 27000 | 0.5035 | 33.4227 | |
|
| 0.5613 | 0.14 | 28000 | 0.4912 | 33.0952 | |
|
| 0.4165 | 0.15 | 29000 | 0.4825 | 32.0155 | |
|
| 0.4736 | 0.15 | 30000 | 0.4716 | 32.0914 | |
|
| 0.4213 | 0.16 | 31000 | 0.4618 | 31.6026 | |
|
| 0.4242 | 0.16 | 32000 | 0.4514 | 30.3757 | |
|
| 0.3837 | 0.17 | 33000 | 0.4448 | 30.3116 | |
|
| 0.4321 | 0.17 | 34000 | 0.4377 | 29.4691 | |
|
| 0.4268 | 0.18 | 35000 | 0.4344 | 29.2057 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.0.dev0 |
|
- Pytorch 2.1.2+cu121 |
|
- Datasets 2.16.2.dev0 |
|
- Tokenizers 0.15.0 |
|
|
