End of training

README.md

@@ -0,0 +1,82 @@
+---
+language:
+- ro
+base_model: iulik-udrik/vreme_model_base
+tags:
+- hf-asr-leaderboard
+- generated_from_trainer
+datasets:
+- iulik-pisik/vreme_horoscop_base
+metrics:
+- wer
+model-index:
+- name: Vreme Model base - finetuned on horoscope
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Horoscop Neti Sandu
+      type: iulik-pisik/vreme_horoscop_base
+      config: default
+      split: None
+      args: 'config: ro, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 17.66853248965685
+---
+
+<!-- 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. -->
+
+# Vreme Model base - finetuned on horoscope
+
+This model is a fine-tuned version of [iulik-udrik/vreme_model_base](https://huggingface.co/iulik-udrik/vreme_model_base) on the Horoscop Neti Sandu dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3471
+- Wer: 17.6685
+
+## 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: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.0111        | 9.71  | 1000 | 0.2991          | 18.3986 |
+| 0.001         | 19.42 | 2000 | 0.3298          | 17.9119 |
+| 0.0006        | 29.13 | 3000 | 0.3422          | 17.4252 |
+| 0.0005        | 38.83 | 4000 | 0.3471          | 17.6685 |
+
+
+### Framework versions
+
+- Transformers 4.39.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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+}

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