|
--- |
|
license: apache-2.0 |
|
tags: |
|
- automatic-speech-recognition |
|
- experiments/data/uwb_atcc/train |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: 0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc |
|
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. --> |
|
|
|
# 0.0ld_0.0ad_0.0attd_0.05fpd_0.075mtp_12mtl_0.0mfp_12mfl_1acc |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the EXPERIMENTS/DATA/UWB_ATCC/TRAIN - NA dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.8470 |
|
- Wer: 0.1898 |
|
|
|
## 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: 24 |
|
- eval_batch_size: 12 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 1000 |
|
- training_steps: 10000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:| |
|
| No log | 1.06 | 500 | 3.1697 | 1.0 | |
|
| 3.1489 | 2.12 | 1000 | 1.4184 | 0.5678 | |
|
| 3.1489 | 3.18 | 1500 | 0.8498 | 0.3366 | |
|
| 0.8499 | 4.25 | 2000 | 0.8089 | 0.2755 | |
|
| 0.8499 | 5.31 | 2500 | 0.7339 | 0.2963 | |
|
| 0.5901 | 6.37 | 3000 | 0.6376 | 0.2402 | |
|
| 0.5901 | 7.43 | 3500 | 0.6890 | 0.2336 | |
|
| 0.4724 | 8.49 | 4000 | 0.6844 | 0.2240 | |
|
| 0.4724 | 9.55 | 4500 | 0.6900 | 0.2222 | |
|
| 0.3981 | 10.62 | 5000 | 0.7051 | 0.2123 | |
|
| 0.3981 | 11.68 | 5500 | 0.6671 | 0.2095 | |
|
| 0.3436 | 12.74 | 6000 | 0.7425 | 0.2049 | |
|
| 0.3436 | 13.8 | 6500 | 0.7135 | 0.1994 | |
|
| 0.2925 | 14.86 | 7000 | 0.7350 | 0.2012 | |
|
| 0.2925 | 15.92 | 7500 | 0.7855 | 0.1945 | |
|
| 0.2525 | 16.99 | 8000 | 0.7933 | 0.1946 | |
|
| 0.2525 | 18.05 | 8500 | 0.8016 | 0.1915 | |
|
| 0.2285 | 19.11 | 9000 | 0.8284 | 0.1907 | |
|
| 0.2285 | 20.17 | 9500 | 0.8275 | 0.1902 | |
|
| 0.2025 | 21.23 | 10000 | 0.8470 | 0.1898 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.24.0 |
|
- Pytorch 1.13.0+cu117 |
|
- Datasets 2.6.1 |
|
- Tokenizers 0.13.2 |
|
|
