File size: 2,071 Bytes
39152b5 |
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 |
---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Medium Pashto
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/fleurs ps_af
type: google/fleurs
config: ps_af
split: test
args: ps_af
metrics:
- name: Wer
type: wer
value: 50.6431598062954
---
<!-- 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 Medium Pashto
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co./openai/whisper-medium) on the google/fleurs ps_af dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2950
- Wer: 50.6432
## 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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0139 | 14.29 | 100 | 1.0302 | 50.1211 |
| 0.0011 | 28.57 | 200 | 1.2129 | 49.7806 |
| 0.0008 | 42.86 | 300 | 1.2581 | 50.3178 |
| 0.0007 | 57.14 | 400 | 1.2850 | 50.5524 |
| 0.0007 | 71.43 | 500 | 1.2950 | 50.6432 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|