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End of training

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README.md CHANGED
@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0445
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- - Wer Score: 18.0
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  ## Model description
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@@ -47,29 +47,32 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine_with_restarts
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  - lr_scheduler_warmup_steps: 100
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- - num_epochs: 85
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Wer Score |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|
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- | 6.2279 | 5.0 | 10 | 6.1543 | 39.6 |
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- | 6.1401 | 10.0 | 20 | 6.0037 | 39.6 |
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- | 5.9375 | 15.0 | 30 | 5.7410 | 39.6 |
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- | 5.6234 | 20.0 | 40 | 5.3648 | 39.6 |
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- | 5.1982 | 25.0 | 50 | 4.8789 | 39.6 |
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- | 4.66 | 30.0 | 60 | 4.2769 | 39.6 |
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- | 4.0101 | 35.0 | 70 | 3.5632 | 39.6 |
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- | 3.2574 | 40.0 | 80 | 2.7503 | 39.6 |
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- | 2.41 | 45.0 | 90 | 1.8801 | 39.6 |
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- | 1.5446 | 50.0 | 100 | 1.0544 | 39.6 |
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- | 0.7865 | 55.0 | 110 | 0.4589 | 39.2 |
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- | 0.33 | 60.0 | 120 | 0.1961 | 19.2 |
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- | 0.1347 | 65.0 | 130 | 0.0977 | 24.4 |
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- | 0.0623 | 70.0 | 140 | 0.0600 | 22.6 |
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- | 0.037 | 75.0 | 150 | 0.0491 | 19.0 |
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- | 0.0281 | 80.0 | 160 | 0.0453 | 18.0 |
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- | 0.0256 | 85.0 | 170 | 0.0445 | 18.0 |
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0219
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+ - Wer Score: 1.2
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: cosine_with_restarts
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  - lr_scheduler_warmup_steps: 100
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+ - num_epochs: 100
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Wer Score |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|
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+ | 0.025 | 5.0 | 10 | 0.0412 | 18.6 |
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+ | 0.0225 | 10.0 | 20 | 0.0377 | 18.8 |
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+ | 0.0182 | 15.0 | 30 | 0.0377 | 20.6 |
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+ | 0.0135 | 20.0 | 40 | 0.0337 | 21.2 |
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+ | 0.0095 | 25.0 | 50 | 0.0314 | 17.0 |
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+ | 0.0067 | 30.0 | 60 | 0.0256 | 17.0 |
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+ | 0.0054 | 35.0 | 70 | 0.0177 | 5.8 |
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+ | 0.006 | 40.0 | 80 | 0.0240 | 37.8 |
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+ | 0.0063 | 45.0 | 90 | 0.0213 | 0.2 |
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+ | 0.0032 | 50.0 | 100 | 0.0222 | 1.8 |
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+ | 0.0021 | 55.0 | 110 | 0.0210 | 1.6 |
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+ | 0.0015 | 60.0 | 120 | 0.0203 | 2.6 |
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+ | 0.0012 | 65.0 | 130 | 0.0211 | 1.4 |
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+ | 0.0011 | 70.0 | 140 | 0.0217 | 1.4 |
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+ | 0.001 | 75.0 | 150 | 0.0218 | 1.2 |
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+ | 0.0009 | 80.0 | 160 | 0.0219 | 1.2 |
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+ | 0.0009 | 85.0 | 170 | 0.0219 | 1.2 |
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+ | 0.0009 | 90.0 | 180 | 0.0219 | 1.2 |
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+ | 0.0009 | 95.0 | 190 | 0.0219 | 1.2 |
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+ | 0.0009 | 100.0 | 200 | 0.0219 | 1.2 |
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  ### Framework versions
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