speech-seq2seq
/

wav2vec2-2-gpt2-medium-no-adapter-frozen-enc

Automatic Speech Recognition Transformers PyTorch TensorBoard

speech-encoder-decoder generated_from_trainer Inference Endpoints

Model card Files Files and versions Metrics Training metrics Community

sanchit-gandhi HF staff commited on Feb 17, 2022

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update model card README.md

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@@ -15,8 +15,8 @@ should probably proofread and complete it, then remove this comment. -->
 This model was trained from scratch on the librispeech_asr dataset.
 It achieves the following results on the evaluation set:
-- Loss: 5.2346
-- Wer: 1.9971
 ## Model description
@@ -35,7 +35,7 @@ More information needed
 ### Training hyperparameters
 The following hyperparameters were used during training:
-- learning_rate: 0.001
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
@@ -51,16 +51,16 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 5.4068        | 0.28  | 500  | 6.0935          | 1.9428 |
-| 5.609         | 0.56  | 1000 | 6.0302          | 1.9717 |
-| 5.5664        | 0.84  | 1500 | 5.6938          | 2.0066 |
-| 4.9162        | 1.12  | 2000 | 5.6412          | 1.9733 |
-| 4.9413        | 1.4   | 2500 | 5.5066          | 1.9556 |
-| 4.7653        | 1.68  | 3000 | 5.3775          | 1.9548 |
-| 4.566         | 1.96  | 3500 | 5.2843          | 1.9802 |
-| 4.4488        | 2.24  | 4000 | 5.3816          | 1.9657 |
-| 3.9933        | 2.52  | 4500 | 5.2800          | 1.9741 |
-| 3.8714        | 2.8   | 5000 | 5.2346          | 1.9971 |
 ### Framework versions

 This model was trained from scratch on the librispeech_asr dataset.
 It achieves the following results on the evaluation set:
+- Loss: 6.5541
+- Wer: 1.9877
 ## Model description
 ### Training hyperparameters
 The following hyperparameters were used during training:
+- learning_rate: 0.0001
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
 | Training Loss | Epoch | Step | Validation Loss | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
+| 1.9364        | 0.28  | 500  | 6.3613          | 1.9833 |
+| 1.941         | 0.56  | 1000 | 5.6974          | 1.9746 |
+| 2.3312        | 0.84  | 1500 | 5.6979          | 1.7345 |
+| 2.8004        | 1.12  | 2000 | 6.0436          | 1.6787 |
+| 3.0003        | 1.4   | 2500 | 6.0955          | 1.7625 |
+| 2.9677        | 1.68  | 3000 | 6.2841          | 1.6731 |
+| 2.2759        | 1.96  | 3500 | 6.3094          | 1.7494 |
+| 2.2989        | 2.24  | 4000 | 6.9891          | 1.9115 |
+| 1.8814        | 2.52  | 4500 | 6.9818          | 1.9832 |
+| 2.658         | 2.8   | 5000 | 6.5541          | 1.9877 |
 ### Framework versions