File size: 2,026 Bytes
ae7ca96 be522a8 ae7ca96 edbaab4 ae7ca96 be522a8 ae7ca96 be522a8 ae7ca96 edbaab4 be522a8 ae7ca96 be522a8 ae7ca96 be522a8 ae7ca96 |
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 |
---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
- hf-asr-leaderboard
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Medium Tajik
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/fleurs
type: google/fleurs
config: tg_tj
split: test
args: tg_tj
metrics:
- name: Wer
type: wer
value: 23.153018764230197
---
<!-- 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 Tajik
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the google/fleurs tg_tj dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9217
- Wer: 23.1530
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0016 | 66.0 | 1000 | 0.6929 | 24.2993 |
| 0.0001 | 133.0 | 2000 | 0.8054 | 23.3022 |
| 0.0001 | 199.0 | 3000 | 0.8652 | 23.2237 |
| 0.0 | 266.0 | 4000 | 0.9019 | 23.2394 |
| 0.0 | 333.0 | 5000 | 0.9217 | 23.1530 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|