End of training

README.md

@@ -1,80 +1,80 @@
----
-license: apache-2.0
-base_model: facebook/wav2vec2-base
-tags:
-- generated_from_trainer
-datasets:
-- ami
-metrics:
-- wer
-model-index:
-- name: my_awesome_asr_mind_model
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: ami
-      type: ami
-      config: ihm
-      split: None
-      args: ihm
-    metrics:
-    - name: Wer
-      type: wer
-      value: 1.0
----
-
-<!-- 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. -->
-
-# my_awesome_asr_mind_model
-
-This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the ami dataset.
-It achieves the following results on the evaluation set:
-- Loss: 3.0325
-- Wer: 1.0
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 1e-05
-- train_batch_size: 8
-- eval_batch_size: 8
-- seed: 42
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 16
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 500
-- training_steps: 2000
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Wer |
-|:-------------:|:-----:|:----:|:---------------:|:---:|
-| 3.1687        | 0.18  | 1000 | 3.2228          | 1.0 |
-| 3.0482        | 0.37  | 2000 | 3.0325          | 1.0 |
-
-
-### Framework versions
-
-- Transformers 4.39.0
-- Pytorch 2.0.0.post304
-- Datasets 2.19.1
-- Tokenizers 0.15.2
+---
+license: apache-2.0
+base_model: facebook/wav2vec2-base
+tags:
+- generated_from_trainer
+datasets:
+- minds14
+metrics:
+- wer
+model-index:
+- name: my_awesome_asr_mind_model
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: minds14
+      type: minds14
+      config: en-US
+      split: None
+      args: en-US
+    metrics:
+    - name: Wer
+      type: wer
+      value: 1.0
+---
+
+<!-- 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. -->
+
+# my_awesome_asr_mind_model
+
+This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.1930
+- Wer: 1.0
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 2000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer |
+|:-------------:|:-----:|:----:|:---------------:|:---:|
+| 3.484         | 200.0 | 1000 | 3.5852          | 1.0 |
+| 3.1067        | 400.0 | 2000 | 3.1930          | 1.0 |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.3.1
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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