File size: 3,170 Bytes
63e5cda 08cd6c8 63e5cda 08cd6c8 63e5cda 08cd6c8 63e5cda e761088 63e5cda e761088 63e5cda e761088 63e5cda |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 |
---
license: apache-2.0
base_model: openai/whisper-base
tags:
- generated_from_trainer
datasets:
- razhan/common_voice_ckb_16
metrics:
- wer
model-index:
- name: whisper-base-ckb
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: razhan/common_voice_ckb_16
type: razhan/common_voice_ckb_16
metrics:
- name: Wer
type: wer
value: 0.12623194275685162
---
<!-- 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. -->
# whisper-base-ckb
This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the razhan/common_voice_ckb_16 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0641
- Wer: 0.1262
## 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: 192
- eval_batch_size: 128
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- total_train_batch_size: 1152
- total_eval_batch_size: 768
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 2300
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.3434 | 1.09 | 100 | 0.3840 | 0.6054 |
| 0.2089 | 2.17 | 200 | 0.2654 | 0.4740 |
| 0.167 | 3.26 | 300 | 0.2246 | 0.4190 |
| 0.1452 | 4.35 | 400 | 0.1964 | 0.3803 |
| 0.1287 | 5.43 | 500 | 0.1788 | 0.3542 |
| 0.1163 | 6.52 | 600 | 0.1650 | 0.3326 |
| 0.1068 | 7.61 | 700 | 0.1560 | 0.3155 |
| 0.1015 | 8.7 | 800 | 0.1489 | 0.3059 |
| 0.0968 | 9.78 | 900 | 0.1440 | 0.2954 |
| 0.0939 | 10.87 | 1000 | 0.1420 | 0.2918 |
| 0.0919 | 11.96 | 1100 | 0.1315 | 0.2742 |
| 0.0839 | 13.04 | 1200 | 0.1217 | 0.2597 |
| 0.0713 | 14.13 | 1300 | 0.1132 | 0.2371 |
| 0.0687 | 15.22 | 1400 | 0.1091 | 0.2372 |
| 0.0647 | 16.3 | 1500 | 0.1022 | 0.2173 |
| 0.059 | 17.39 | 1600 | 0.0967 | 0.2043 |
| 0.0539 | 18.48 | 1700 | 0.0897 | 0.1929 |
| 0.0518 | 19.57 | 1800 | 0.0827 | 0.1718 |
| 0.0495 | 20.65 | 1900 | 0.0787 | 0.1667 |
| 0.0444 | 21.74 | 2000 | 0.0718 | 0.1469 |
| 0.0392 | 22.83 | 2100 | 0.0671 | 0.1368 |
| 0.0335 | 23.91 | 2200 | 0.0645 | 0.1263 |
| 0.0292 | 25.0 | 2300 | 0.0641 | 0.1262 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0
|