|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: Samuael/geez-asr |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- alffa_amharic |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: ethiopic-asr |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: alffa_amharic |
|
type: alffa_amharic |
|
config: clean |
|
split: None |
|
args: clean |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.14692601597777005 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# ethiopic-asr |
|
|
|
This model is a fine-tuned version of [Samuael/geez-asr](https://huggingface.co/Samuael/geez-asr) on the alffa_amharic dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1301 |
|
- Wer: 0.1469 |
|
- Phoneme Cer: 0.0296 |
|
- Cer: 0.0416 |
|
|
|
## 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: 3e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 100 |
|
- num_epochs: 1 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Phoneme Cer | Cer | |
|
|:-------------:|:------:|:----:|:---------------:|:------:|:-----------:|:------:| |
|
| No log | 0.0442 | 200 | 3.2216 | 1.0 | 1.0 | 1.0 | |
|
| No log | 0.0883 | 400 | 3.1164 | 1.0 | 1.0 | 1.0 | |
|
| 4.1769 | 0.1325 | 600 | 0.9628 | 0.5476 | 0.1141 | 0.1609 | |
|
| 4.1769 | 0.1767 | 800 | 0.3181 | 0.2150 | 0.0430 | 0.0607 | |
|
| 0.8455 | 0.2208 | 1000 | 0.2195 | 0.1759 | 0.0353 | 0.0503 | |
|
| 0.8455 | 0.2650 | 1200 | 0.1913 | 0.1846 | 0.0365 | 0.0520 | |
|
| 0.8455 | 0.3092 | 1400 | 0.1699 | 0.1591 | 0.0322 | 0.0454 | |
|
| 0.2929 | 0.3534 | 1600 | 0.1603 | 0.1572 | 0.0316 | 0.0442 | |
|
| 0.2929 | 0.3975 | 1800 | 0.1503 | 0.1567 | 0.0315 | 0.0442 | |
|
| 0.2392 | 0.4417 | 2000 | 0.1476 | 0.1587 | 0.0318 | 0.0446 | |
|
| 0.2392 | 0.4859 | 2200 | 0.1449 | 0.1565 | 0.0312 | 0.0438 | |
|
| 0.2392 | 0.5300 | 2400 | 0.1409 | 0.1537 | 0.0308 | 0.0427 | |
|
| 0.2166 | 0.5742 | 2600 | 0.1395 | 0.1551 | 0.0308 | 0.0428 | |
|
| 0.2166 | 0.6184 | 2800 | 0.1345 | 0.1469 | 0.0290 | 0.0410 | |
|
| 0.2068 | 0.6625 | 3000 | 0.1331 | 0.1509 | 0.0297 | 0.0419 | |
|
| 0.2068 | 0.7067 | 3200 | 0.1346 | 0.1518 | 0.0301 | 0.0421 | |
|
| 0.2068 | 0.7509 | 3400 | 0.1335 | 0.1507 | 0.0303 | 0.0426 | |
|
| 0.2037 | 0.7951 | 3600 | 0.1312 | 0.1471 | 0.0297 | 0.0415 | |
|
| 0.2037 | 0.8392 | 3800 | 0.1303 | 0.1438 | 0.0289 | 0.0406 | |
|
| 0.1985 | 0.8834 | 4000 | 0.1300 | 0.1457 | 0.0292 | 0.0410 | |
|
| 0.1985 | 0.9276 | 4200 | 0.1303 | 0.1471 | 0.0295 | 0.0414 | |
|
| 0.1985 | 0.9717 | 4400 | 0.1301 | 0.1469 | 0.0296 | 0.0416 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.45.1 |
|
- Pytorch 2.4.1+cu121 |
|
- Datasets 3.0.1 |
|
- Tokenizers 0.20.0 |
|
|
