Training in progress, step 500

.gitattributes

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README.md

@@ -1,9 +1,12 @@
 ---
+language:
+- en
 license: apache-2.0
 tags:
+- audio
+- speech
+- wav2vec2
 - generated_from_trainer
-metrics:
-- wer
 model-index:
 - name: torgo_xlsr_finetune_M01
   results: []
@@ -14,10 +17,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 # torgo_xlsr_finetune_M01
 
-This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.7808
-- Wer: 0.5966
+This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the torgo dataset.
 
 ## Model description
 
@@ -37,90 +37,19 @@ 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: 4
+- eval_batch_size: 4
 - seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 8
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 1000
-- num_epochs: 30
-
-### Training results
-
-| Training Loss | Epoch | Step  | Validation Loss | Wer    |
-|:-------------:|:-----:|:-----:|:---------------:|:------:|
-| 3.3568        | 0.45  | 500   | 3.2373          | 1.0    |
-| 2.6662        | 0.89  | 1000  | 1.9097          | 0.9707 |
-| 1.4433        | 1.34  | 1500  | 1.8284          | 0.8819 |
-| 1.0086        | 1.79  | 2000  | 1.5207          | 0.8233 |
-| 0.8253        | 2.24  | 2500  | 1.5046          | 0.7888 |
-| 0.7438        | 2.68  | 3000  | 1.4814          | 0.7457 |
-| 0.6364        | 3.13  | 3500  | 1.5690          | 0.7448 |
-| 0.593         | 3.58  | 4000  | 1.7702          | 0.7293 |
-| 0.555         | 4.03  | 4500  | 1.5775          | 0.7078 |
-| 0.479         | 4.47  | 5000  | 1.4384          | 0.7026 |
-| 0.4735        | 4.92  | 5500  | 1.6368          | 0.6940 |
-| 0.4284        | 5.37  | 6000  | 1.9717          | 0.6879 |
-| 0.429         | 5.81  | 6500  | 1.4882          | 0.6578 |
-| 0.4128        | 6.26  | 7000  | 1.4697          | 0.6664 |
-| 0.3869        | 6.71  | 7500  | 1.5555          | 0.6647 |
-| 0.3725        | 7.16  | 8000  | 1.7755          | 0.6664 |
-| 0.3104        | 7.6   | 8500  | 1.4753          | 0.65   |
-| 0.3355        | 8.05  | 9000  | 1.5212          | 0.6526 |
-| 0.3119        | 8.5   | 9500  | 1.6810          | 0.6345 |
-| 0.3186        | 8.94  | 10000 | 2.2611          | 0.6534 |
-| 0.3065        | 9.39  | 10500 | 1.2431          | 0.6397 |
-| 0.2862        | 9.84  | 11000 | 1.5408          | 0.6371 |
-| 0.2628        | 10.29 | 11500 | 2.0784          | 0.6474 |
-| 0.2792        | 10.73 | 12000 | 1.6698          | 0.6293 |
-| 0.2944        | 11.18 | 12500 | 1.7610          | 0.6336 |
-| 0.237         | 11.63 | 13000 | 1.5215          | 0.6371 |
-| 0.2471        | 12.08 | 13500 | 1.6935          | 0.65   |
-| 0.2154        | 12.52 | 14000 | 1.7569          | 0.6319 |
-| 0.2367        | 12.97 | 14500 | 1.6718          | 0.6284 |
-| 0.2499        | 13.42 | 15000 | 1.4102          | 0.6302 |
-| 0.2306        | 13.86 | 15500 | 1.5523          | 0.6147 |
-| 0.2337        | 14.31 | 16000 | 1.8419          | 0.6129 |
-| 0.206         | 14.76 | 16500 | 1.5285          | 0.6069 |
-| 0.2098        | 15.21 | 17000 | 1.7365          | 0.6198 |
-| 0.1994        | 15.65 | 17500 | 1.6756          | 0.6052 |
-| 0.1943        | 16.1  | 18000 | 1.9950          | 0.6241 |
-| 0.2077        | 16.55 | 18500 | 1.6966          | 0.6121 |
-| 0.2135        | 16.99 | 19000 | 1.7379          | 0.6233 |
-| 0.1721        | 17.44 | 19500 | 2.1036          | 0.6147 |
-| 0.1876        | 17.89 | 20000 | 1.7061          | 0.6129 |
-| 0.187         | 18.34 | 20500 | 1.7549          | 0.5897 |
-| 0.1699        | 18.78 | 21000 | 1.7215          | 0.6009 |
-| 0.1833        | 19.23 | 21500 | 1.5892          | 0.6069 |
-| 0.1545        | 19.68 | 22000 | 1.7657          | 0.6155 |
-| 0.1624        | 20.13 | 22500 | 1.5143          | 0.6103 |
-| 0.1631        | 20.57 | 23000 | 1.4752          | 0.5974 |
-| 0.1476        | 21.02 | 23500 | 1.5408          | 0.6    |
-| 0.141         | 21.47 | 24000 | 1.7880          | 0.6112 |
-| 0.1617        | 21.91 | 24500 | 1.7662          | 0.6190 |
-| 0.1435        | 22.36 | 25000 | 1.8012          | 0.6034 |
-| 0.1456        | 22.81 | 25500 | 1.7721          | 0.6052 |
-| 0.147         | 23.26 | 26000 | 1.6913          | 0.6    |
-| 0.137         | 23.7  | 26500 | 1.8138          | 0.5983 |
-| 0.1269        | 24.15 | 27000 | 2.0274          | 0.5974 |
-| 0.1203        | 24.6  | 27500 | 1.8193          | 0.5879 |
-| 0.1321        | 25.04 | 28000 | 1.7929          | 0.5853 |
-| 0.1333        | 25.49 | 28500 | 1.9791          | 0.6017 |
-| 0.1061        | 25.94 | 29000 | 1.7340          | 0.5957 |
-| 0.1099        | 26.39 | 29500 | 1.7547          | 0.6017 |
-| 0.111         | 26.83 | 30000 | 1.7777          | 0.5991 |
-| 0.1239        | 27.28 | 30500 | 1.7383          | 0.5991 |
-| 0.1179        | 27.73 | 31000 | 1.8627          | 0.6009 |
-| 0.0995        | 28.18 | 31500 | 1.7775          | 0.5966 |
-| 0.0924        | 28.62 | 32000 | 1.8651          | 0.5966 |
-| 0.1144        | 29.07 | 32500 | 1.7918          | 0.5974 |
-| 0.1082        | 29.52 | 33000 | 1.7697          | 0.5957 |
-| 0.1008        | 29.96 | 33500 | 1.7808          | 0.5966 |
-
+- num_epochs: 20
 
 ### Framework versions
 
 - Transformers 4.26.1
-- Pytorch 2.1.0+cu118
-- Datasets 2.15.0
+- Pytorch 2.1.2
+- Datasets 2.16.1
 - Tokenizers 0.13.3

config.json

@@ -49,7 +49,7 @@
   "feat_extract_activation": "gelu",
   "feat_extract_dropout": 0.0,
   "feat_extract_norm": "layer",
-  "feat_proj_dropout": 0.1,
+  "feat_proj_dropout": 0.0,
   "feat_quantizer_dropout": 0.0,
   "final_dropout": 0.0,
   "gradient_checkpointing": false,
@@ -72,7 +72,7 @@
   "mask_time_min_masks": 2,
   "mask_time_min_space": 1,
   "mask_time_other": 0.0,
-  "mask_time_prob": 0.075,
+  "mask_time_prob": 0.05,
   "mask_time_selection": "static",
   "model_type": "wav2vec2",
   "num_adapter_layers": 3,
@@ -85,7 +85,7 @@
   "num_hidden_layers": 24,
   "num_negatives": 100,
   "output_hidden_size": 1024,
-  "pad_token_id": 29,
+  "pad_token_id": 0,
   "proj_codevector_dim": 768,
   "tdnn_dilation": [
     1,

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