End of training

README.md

@@ -1,8 +1,8 @@
 ---
 license: apache-2.0
+base_model: facebook/wav2vec2-base
 tags:
 - generated_from_trainer
-base_model: mattbonnell/wav2vec2-base-wonders-phonemes
 datasets:
 - transcribed_calls
 metrics:
@@ -11,8 +11,8 @@ model-index:
 - name: wav2vec2-base-wonders-phonemes
   results:
   - task:
-      type: automatic-speech-recognition
       name: Automatic Speech Recognition
+      type: automatic-speech-recognition
     dataset:
       name: transcribed_calls
       type: transcribed_calls
@@ -20,9 +20,9 @@ model-index:
       split: None
       args: default
     metrics:
-    - type: wer
+    - name: Wer
+      type: wer
       value: 1.0
-      name: Wer
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,9 +30,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 # wav2vec2-base-wonders-phonemes
 
-This model is a fine-tuned version of [mattbonnell/wav2vec2-base-wonders-phonemes](https://huggingface.co/mattbonnell/wav2vec2-base-wonders-phonemes) on the transcribed_calls dataset.
+This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the transcribed_calls dataset.
 It achieves the following results on the evaluation set:
-- Loss: nan
+- Loss: 4.1008
 - Wer: 1.0
 
 ## Model description
@@ -53,31 +53,60 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0001
-- train_batch_size: 8
-- eval_batch_size: 8
+- train_batch_size: 2
+- eval_batch_size: 2
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 100
+- lr_scheduler_warmup_steps: 1000
 - num_epochs: 30
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer |
-|:-------------:|:-----:|:----:|:---------------:|:---:|
-| 0.0           | 2.5   | 5    | nan             | 1.0 |
-| 0.0           | 5.0   | 10   | nan             | 1.0 |
-| 0.0           | 7.5   | 15   | nan             | 1.0 |
-| 0.0           | 10.0  | 20   | nan             | 1.0 |
-| 0.0           | 12.5  | 25   | nan             | 1.0 |
-| 0.0           | 15.0  | 30   | nan             | 1.0 |
-| 0.0           | 17.5  | 35   | nan             | 1.0 |
-| 0.0           | 20.0  | 40   | nan             | 1.0 |
-| 0.0           | 22.5  | 45   | nan             | 1.0 |
-| 0.0           | 25.0  | 50   | nan             | 1.0 |
-| 0.0           | 27.5  | 55   | nan             | 1.0 |
-| 0.0           | 30.0  | 60   | nan             | 1.0 |
+| Training Loss | Epoch | Step  | Validation Loss | Wer |
+|:-------------:|:-----:|:-----:|:---------------:|:---:|
+| 3.5174        | 0.73  | 2000  | 4.1615          | 1.0 |
+| 3.3943        | 1.45  | 4000  | 4.2182          | 1.0 |
+| 3.3465        | 2.18  | 6000  | 4.2119          | 1.0 |
+| 3.3343        | 2.9   | 8000  | 4.2471          | 1.0 |
+| 3.3546        | 3.63  | 10000 | 4.0944          | 1.0 |
+| 3.7063        | 4.36  | 12000 | 4.1280          | 1.0 |
+| 3.352         | 5.08  | 14000 | 4.0348          | 1.0 |
+| 3.4307        | 5.81  | 16000 | 4.1120          | 1.0 |
+| 3.3496        | 6.54  | 18000 | 4.0892          | 1.0 |
+| 3.3681        | 7.26  | 20000 | 4.1087          | 1.0 |
+| 3.3285        | 7.99  | 22000 | 4.0877          | 1.0 |
+| 3.4597        | 8.71  | 24000 | 4.1041          | 1.0 |
+| 3.3582        | 9.44  | 26000 | 4.0729          | 1.0 |
+| 3.3898        | 10.17 | 28000 | 4.0884          | 1.0 |
+| 3.4005        | 10.89 | 30000 | 4.1275          | 1.0 |
+| 3.3362        | 11.62 | 32000 | 4.0973          | 1.0 |
+| 3.4801        | 12.35 | 34000 | 4.0916          | 1.0 |
+| 3.3902        | 13.07 | 36000 | 4.0946          | 1.0 |
+| 3.3554        | 13.8  | 38000 | 4.1222          | 1.0 |
+| 3.5212        | 14.52 | 40000 | 4.0763          | 1.0 |
+| 3.3771        | 15.25 | 42000 | 4.1347          | 1.0 |
+| 3.333         | 15.98 | 44000 | 4.1217          | 1.0 |
+| 3.3605        | 16.7  | 46000 | 4.1400          | 1.0 |
+| 3.3526        | 17.43 | 48000 | 4.1099          | 1.0 |
+| 3.3134        | 18.16 | 50000 | 4.1327          | 1.0 |
+| 3.5681        | 18.88 | 52000 | 4.1114          | 1.0 |
+| 3.3497        | 19.61 | 54000 | 4.1006          | 1.0 |
+| 4.0995        | 20.33 | 56000 | 4.0972          | 1.0 |
+| 3.3377        | 21.06 | 58000 | 4.1035          | 1.0 |
+| 3.355         | 21.79 | 60000 | 4.1022          | 1.0 |
+| 3.5084        | 22.51 | 62000 | 4.1252          | 1.0 |
+| 3.3558        | 23.24 | 64000 | 4.1028          | 1.0 |
+| 3.3328        | 23.97 | 66000 | 4.0976          | 1.0 |
+| 3.8824        | 24.69 | 68000 | 4.1290          | 1.0 |
+| 3.3406        | 25.42 | 70000 | 4.1173          | 1.0 |
+| 3.9972        | 26.14 | 72000 | 4.1178          | 1.0 |
+| 3.4915        | 26.87 | 74000 | 4.0926          | 1.0 |
+| 3.5408        | 27.6  | 76000 | 4.1069          | 1.0 |
+| 3.6864        | 28.32 | 78000 | 4.1030          | 1.0 |
+| 3.326         | 29.05 | 80000 | 4.1058          | 1.0 |
+| 3.3171        | 29.77 | 82000 | 4.1008          | 1.0 |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ec48c779376af4a036b21d261fa5778fa6ea811701f9a941bfff403620f7f0de
+oid sha256:bd324e2dc52f9b1923079a9191f6a649b3f30538c80af961968cff43f749ee72
 size 377657268