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---
library_name: transformers
language:
- lv
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper medium LV - Felikss Kleins-{timestamp}
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
config: lv
split: None
args: 'config: lv, split: test'
metrics:
- name: Wer
type: wer
value: 10.601196845400864
---
<!-- 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 LV - Felikss Kleins-{timestamp}
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2428
- Wer: 10.6012
## 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: 32
- eval_batch_size: 32
- 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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| No log | 0.02 | 200 | 0.2930 | 22.3576 |
| 0.9797 | 1.0116 | 400 | 0.2359 | 18.2083 |
| 0.357 | 2.0033 | 600 | 0.2274 | 16.4665 |
| 0.2582 | 2.0233 | 800 | 0.2111 | 15.6402 |
| 0.1718 | 3.0149 | 1000 | 0.2135 | 14.9883 |
| 0.1718 | 4.0066 | 1200 | 0.2090 | 14.2294 |
| 0.1355 | 4.0266 | 1400 | 0.2193 | 13.5537 |
| 0.1024 | 5.0183 | 1600 | 0.2255 | 14.5048 |
| 0.0836 | 6.0099 | 1800 | 0.2145 | 12.9751 |
| 0.0699 | 7.0015 | 2000 | 0.2232 | 13.2129 |
| 0.0699 | 7.0216 | 2200 | 0.2181 | 12.7155 |
| 0.0598 | 8.0132 | 2400 | 0.2192 | 12.7076 |
| 0.054 | 9.0048 | 2600 | 0.2348 | 13.0048 |
| 0.0452 | 9.0249 | 2800 | 0.2241 | 13.0940 |
| 0.0433 | 10.0165 | 3000 | 0.2406 | 12.6362 |
| 0.0433 | 11.0082 | 3200 | 0.2283 | 12.5332 |
| 0.0377 | 11.0282 | 3400 | 0.2293 | 12.2201 |
| 0.0317 | 12.0198 | 3600 | 0.2323 | 12.6144 |
| 0.0297 | 13.0114 | 3800 | 0.2309 | 12.2974 |
| 0.0267 | 14.0031 | 4000 | 0.2342 | 11.9011 |
| 0.0267 | 14.0231 | 4200 | 0.2286 | 12.1171 |
| 0.0243 | 15.0147 | 4400 | 0.2364 | 12.0854 |
| 0.0218 | 16.0064 | 4600 | 0.2405 | 12.1805 |
| 0.021 | 16.0264 | 4800 | 0.2422 | 12.0338 |
| 0.0173 | 17.0180 | 5000 | 0.2416 | 11.9387 |
| 0.0173 | 18.0097 | 5200 | 0.2421 | 12.0180 |
| 0.0175 | 19.0013 | 5400 | 0.2385 | 11.6613 |
| 0.0161 | 19.0214 | 5600 | 0.2442 | 11.9090 |
| 0.0136 | 20.013 | 5800 | 0.2411 | 11.4513 |
| 0.0135 | 21.0047 | 6000 | 0.2470 | 12.0418 |
| 0.0135 | 21.0247 | 6200 | 0.2446 | 11.5246 |
| 0.0117 | 22.0163 | 6400 | 0.2466 | 11.7386 |
| 0.0111 | 23.0080 | 6600 | 0.2498 | 12.0715 |
| 0.01 | 23.0280 | 6800 | 0.2487 | 12.0596 |
| 0.0094 | 24.0196 | 7000 | 0.2431 | 11.4315 |
| 0.0094 | 25.0113 | 7200 | 0.2460 | 11.5702 |
| 0.009 | 26.0029 | 7400 | 0.2436 | 11.2293 |
| 0.0077 | 26.0229 | 7600 | 0.2467 | 11.3423 |
| 0.007 | 27.0145 | 7800 | 0.2439 | 11.0054 |
| 0.0071 | 28.0062 | 8000 | 0.2430 | 11.1996 |
| 0.0071 | 28.0262 | 8200 | 0.2458 | 11.1798 |
| 0.0063 | 29.0178 | 8400 | 0.2456 | 11.0847 |
| 0.0049 | 30.0095 | 8600 | 0.2450 | 11.1303 |
| 0.0049 | 31.0011 | 8800 | 0.2467 | 11.0530 |
| 0.0053 | 31.0211 | 9000 | 0.2448 | 11.1085 |
| 0.0053 | 32.0128 | 9200 | 0.2467 | 11.2650 |
| 0.0041 | 33.0044 | 9400 | 0.2444 | 11.0728 |
| 0.0045 | 33.0245 | 9600 | 0.2426 | 10.6547 |
| 0.0036 | 34.0161 | 9800 | 0.2427 | 10.5972 |
| 0.004 | 35.0078 | 10000 | 0.2428 | 10.6012 |
### Framework versions
- Transformers 4.45.0.dev0
- Pytorch 2.0.1
- Datasets 3.0.0
- Tokenizers 0.19.1
|