--- license: cc-by-nc-4.0 base_model: facebook/mms-1b-all tags: - generated_from_trainer metrics: - wer model-index: - name: wav2vec2-large-mms-1b-kazakh-speech2ner-ksc_t-16b-8ep results: [] --- # wav2vec2-large-mms-1b-kazakh-speech2ner-ksc_t-16b-8ep This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2356 - Wer: 0.3093 ## 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: 16 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 1000 - num_epochs: 8 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:-----:|:---------------:|:------:| | 5.1 | 0.22 | 2000 | 5.0320 | 1.0014 | | 3.8579 | 0.43 | 4000 | 3.8757 | 1.0001 | | 3.617 | 0.65 | 6000 | 3.6434 | 1.0001 | | 3.56 | 0.87 | 8000 | 3.5268 | 0.9999 | | 3.4363 | 1.09 | 10000 | 3.4524 | 0.9999 | | 3.3759 | 1.3 | 12000 | 3.4010 | 0.9999 | | 3.3024 | 1.52 | 14000 | 3.3323 | 1.0000 | | 2.721 | 1.74 | 16000 | 2.4051 | 1.0048 | | 0.3937 | 1.96 | 18000 | 0.3398 | 0.3681 | | 0.3456 | 2.17 | 20000 | 0.3013 | 0.3523 | | 0.3269 | 2.39 | 22000 | 0.2836 | 0.3410 | | 0.3275 | 2.61 | 24000 | 0.2738 | 0.3346 | | 0.3053 | 2.83 | 26000 | 0.2667 | 0.3294 | | 0.3041 | 3.04 | 28000 | 0.2619 | 0.3263 | | 0.3084 | 3.26 | 30000 | 0.2574 | 0.3230 | | 0.2915 | 3.48 | 32000 | 0.2547 | 0.3207 | | 0.2865 | 3.69 | 34000 | 0.2521 | 0.3187 | | 0.2814 | 3.91 | 36000 | 0.2500 | 0.3172 | | 0.2961 | 4.13 | 38000 | 0.2479 | 0.3159 | | 0.3037 | 4.35 | 40000 | 0.2464 | 0.3147 | | 0.3023 | 4.56 | 42000 | 0.2448 | 0.3148 | | 0.2977 | 4.78 | 44000 | 0.2433 | 0.3139 | | 0.2933 | 5.0 | 46000 | 0.2422 | 0.3133 | | 0.2838 | 5.22 | 48000 | 0.2413 | 0.3120 | | 0.2833 | 5.43 | 50000 | 0.2401 | 0.3123 | | 0.2774 | 5.65 | 52000 | 0.2398 | 0.3112 | | 0.2813 | 5.87 | 54000 | 0.2389 | 0.3111 | | 0.2779 | 6.08 | 56000 | 0.2380 | 0.3108 | | 0.2872 | 6.3 | 58000 | 0.2376 | 0.3106 | | 0.2758 | 6.52 | 60000 | 0.2372 | 0.3106 | | 0.275 | 6.74 | 62000 | 0.2369 | 0.3095 | | 0.2749 | 6.95 | 64000 | 0.2364 | 0.3100 | | 0.2828 | 7.17 | 66000 | 0.2362 | 0.3098 | | 0.2749 | 7.39 | 68000 | 0.2359 | 0.3093 | | 0.2775 | 7.61 | 70000 | 0.2358 | 0.3093 | | 0.2744 | 7.82 | 72000 | 0.2356 | 0.3093 | ### Framework versions - Transformers 4.33.0.dev0 - Pytorch 2.0.1+cu117 - Datasets 2.13.1 - Tokenizers 0.13.3