Training in progress, step 100

README.md

@@ -1,26 +1,23 @@
 ---
-language:
-- en
 license: mit
 base_model: microsoft/speecht5_tts
 tags:
-- en_accent,mozilla,t5,common_voice_1_0
 - generated_from_trainer
 datasets:
-- mozilla-foundation/common_voice_1_0
+- voxpopuli
 model-index:
-- name: SpeechT5 TTS English Accented
+- name: speecht5_tts
   results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# SpeechT5 TTS English Accented
+# speecht5_tts
 
-This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the Common Voice dataset.
+This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the voxpopuli dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6385
+- Loss: 0.7094
 
 ## Model description
 
@@ -40,21 +37,25 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 8
+- train_batch_size: 32
 - eval_batch_size: 8
 - seed: 42
 - gradient_accumulation_steps: 2
-- total_train_batch_size: 16
+- total_train_batch_size: 64
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- training_steps: 100
+- lr_scheduler_warmup_steps: 500
+- training_steps: 4000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss |
-|:-------------:|:-----:|:----:|:---------------:|
-| 0.7681        | 0.8   | 100  | 0.6385          |
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 0.1945        | 1000.0 | 1000 | 0.6777          |
+| 0.1781        | 2000.0 | 2000 | 0.6907          |
+| 0.1697        | 3000.0 | 3000 | 0.7122          |
+| 0.1699        | 4000.0 | 4000 | 0.7094          |
 
 
 ### Framework versions

model.safetensors

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training_args.bin

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