speech-seq2seq
/

wav2vec2-2-bart-large-no-adapter-frozen-enc

Automatic Speech Recognition

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 18, 2022

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1 Parent(s): e698ebd

update model card README.md

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@@ -15,7 +15,7 @@ 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: 18.0808
 - Wer: 1.0
 ## Model description
@@ -35,7 +35,7 @@ More information needed
 ### Training hyperparameters
 The following hyperparameters were used during training:
-- learning_rate: 0.0003
 - 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    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 6.1986        | 0.28  | 500  | 8.8308          | 1.0007 |
-| 5.1211        | 0.56  | 1000 | 12.3407         | 1.0025 |
-| 4.4472        | 0.84  | 1500 | 14.1840         | 1.0025 |
-| 5.4118        | 1.12  | 2000 | 11.8314         | 1.0469 |
-| 5.2992        | 1.4   | 2500 | 14.5952         | 1.0047 |
-| 5.1043        | 1.68  | 3000 | 13.5353         | 1.0055 |
-| 5.4595        | 1.96  | 3500 | 16.3452         | 1.0020 |
-| 4.5259        | 2.24  | 4000 | 17.2874         | 1.0018 |
-| 4.6534        | 2.52  | 4500 | 18.2703         | 1.0010 |
-| 4.3052        | 2.8   | 5000 | 18.0808         | 1.0    |
 ### Framework versions

 This model was trained from scratch on the librispeech_asr dataset.
 It achieves the following results on the evaluation set:
+- Loss: 18.7898
 - Wer: 1.0
 ## 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    |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
+| 6.5396        | 0.28  | 500  | 9.0401          | 1.0120 |
+| 5.898         | 0.56  | 1000 | 9.3199          | 1.0    |
+| 4.9595        | 0.84  | 1500 | 8.4434          | 1.4563 |
+| 5.7082        | 1.12  | 2000 | 15.1805         | 1.0000 |
+| 5.4377        | 1.4   | 2500 | 15.7984         | 1.0021 |
+| 5.5941        | 1.68  | 3000 | 18.4928         | 1.0    |
+| 5.0662        | 1.96  | 3500 | 17.4886         | 1.0000 |
+| 4.8363        | 2.24  | 4000 | 18.9458         | 1.0    |
+| 4.7908        | 2.52  | 4500 | 18.2794         | 1.0006 |
+| 4.679         | 2.8   | 5000 | 18.7898         | 1.0    |
 ### Framework versions