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wav2vec2-large-xlsr-sw

Automatic Speech Recognition
Transformers
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wav2vec2
Generated from Trainer
Eval Results
Inference Endpoints
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  1. README.md +111 -0
  2. model.safetensors +1 -1
  3. runs/Jan16_16-42-18_hades-prod01/events.out.tfevents.1705423625.hades-prod01.1678284.0 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-large-xlsr-53
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - common_voice_11_0
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: wav2vec2-large-xlsr-sw
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: common_voice_11_0
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+ type: common_voice_11_0
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+ config: sw
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+ split: test
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+ args: sw
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.3230712635221355
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # wav2vec2-large-xlsr-sw
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_11_0 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4334
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+ - Wer: 0.3231
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0003
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 30
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 5.3405 | 0.88 | 400 | 2.8882 | 1.0000 |
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+ | 1.083 | 1.77 | 800 | 0.5223 | 0.5849 |
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+ | 0.4721 | 2.65 | 1200 | 0.3921 | 0.4667 |
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+ | 0.3793 | 3.54 | 1600 | 0.3725 | 0.4257 |
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+ | 0.3264 | 4.42 | 2000 | 0.3646 | 0.4179 |
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+ | 0.294 | 5.31 | 2400 | 0.3542 | 0.4104 |
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+ | 0.2623 | 6.19 | 2800 | 0.3576 | 0.3892 |
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+ | 0.2408 | 7.08 | 3200 | 0.3516 | 0.3876 |
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+ | 0.2229 | 7.96 | 3600 | 0.3580 | 0.3877 |
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+ | 0.206 | 8.85 | 4000 | 0.3466 | 0.3683 |
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+ | 0.1991 | 9.73 | 4400 | 0.3306 | 0.3783 |
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+ | 0.1863 | 10.62 | 4800 | 0.3605 | 0.3707 |
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+ | 0.1743 | 11.5 | 5200 | 0.3483 | 0.3703 |
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+ | 0.1678 | 12.39 | 5600 | 0.3645 | 0.3618 |
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+ | 0.1547 | 13.27 | 6000 | 0.3671 | 0.3589 |
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+ | 0.152 | 14.16 | 6400 | 0.3733 | 0.3568 |
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+ | 0.144 | 15.04 | 6800 | 0.3684 | 0.3486 |
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+ | 0.136 | 15.93 | 7200 | 0.3558 | 0.3493 |
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+ | 0.1262 | 16.81 | 7600 | 0.3748 | 0.3486 |
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+ | 0.1222 | 17.7 | 8000 | 0.3774 | 0.3466 |
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+ | 0.1164 | 18.58 | 8400 | 0.3840 | 0.3427 |
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+ | 0.1108 | 19.47 | 8800 | 0.3988 | 0.3438 |
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+ | 0.1072 | 20.35 | 9200 | 0.4020 | 0.3384 |
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+ | 0.1008 | 21.24 | 9600 | 0.4013 | 0.3375 |
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+ | 0.0982 | 22.12 | 10000 | 0.4162 | 0.3361 |
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+ | 0.0951 | 23.01 | 10400 | 0.4107 | 0.3346 |
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+ | 0.0923 | 23.89 | 10800 | 0.4248 | 0.3337 |
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+ | 0.0866 | 24.78 | 11200 | 0.4151 | 0.3295 |
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+ | 0.0875 | 25.66 | 11600 | 0.4211 | 0.3310 |
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+ | 0.0813 | 26.55 | 12000 | 0.4303 | 0.3290 |
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+ | 0.0775 | 27.43 | 12400 | 0.4334 | 0.3249 |
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+ | 0.0759 | 28.32 | 12800 | 0.4312 | 0.3240 |
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+ | 0.0758 | 29.2 | 13200 | 0.4334 | 0.3231 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.0.dev0
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+ - Pytorch 2.1.1+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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