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training completed[dev]: 1024 128

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README.md CHANGED
@@ -18,12 +18,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0100
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- - Rouge1: 0.6961
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- - Rouge2: 0.4369
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- - Rougel: 0.6352
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- - Rougelsum: 0.6352
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- - Wer: 0.4562
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  ## Model description
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@@ -48,20 +48,28 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 1
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:------:|
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- | No log | 0.13 | 250 | 1.2180 | 0.6601 | 0.3882 | 0.5954 | 0.5952 | 0.4981 |
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- | 2.1099 | 0.27 | 500 | 1.1152 | 0.68 | 0.4133 | 0.6165 | 0.6164 | 0.4806 |
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- | 2.1099 | 0.4 | 750 | 1.0765 | 0.6817 | 0.4177 | 0.6181 | 0.618 | 0.4723 |
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- | 1.1853 | 0.53 | 1000 | 1.0552 | 0.6915 | 0.4283 | 0.6284 | 0.6283 | 0.4664 |
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- | 1.1853 | 0.66 | 1250 | 1.0315 | 0.6958 | 0.4327 | 0.6328 | 0.6326 | 0.4622 |
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- | 1.1179 | 0.8 | 1500 | 1.0227 | 0.6912 | 0.4317 | 0.6297 | 0.6296 | 0.4582 |
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- | 1.1179 | 0.93 | 1750 | 1.0100 | 0.6961 | 0.4369 | 0.6352 | 0.6352 | 0.4562 |
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/bart-large](https://huggingface.co/facebook/bart-large) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9558
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+ - Rouge1: 0.7069
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+ - Rouge2: 0.4544
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+ - Rougel: 0.6489
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+ - Rougelsum: 0.6489
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+ - Wer: 0.4398
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  ## Model description
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 2
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Wer |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:------:|
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+ | No log | 0.13 | 250 | 1.2224 | 0.665 | 0.3911 | 0.6 | 0.6001 | 0.4993 |
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+ | 2.0905 | 0.27 | 500 | 1.1190 | 0.6743 | 0.4083 | 0.6103 | 0.6104 | 0.4809 |
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+ | 2.0905 | 0.4 | 750 | 1.0832 | 0.6818 | 0.418 | 0.6178 | 0.6178 | 0.4726 |
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+ | 1.188 | 0.53 | 1000 | 1.0541 | 0.6871 | 0.4246 | 0.6242 | 0.6242 | 0.4675 |
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+ | 1.188 | 0.66 | 1250 | 1.0352 | 0.6881 | 0.4283 | 0.6269 | 0.6268 | 0.4628 |
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+ | 1.1172 | 0.8 | 1500 | 1.0291 | 0.6912 | 0.4319 | 0.6303 | 0.6303 | 0.4586 |
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+ | 1.1172 | 0.93 | 1750 | 1.0079 | 0.7001 | 0.4406 | 0.6396 | 0.6397 | 0.4543 |
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+ | 1.0803 | 1.06 | 2000 | 0.9957 | 0.6939 | 0.4396 | 0.6359 | 0.6359 | 0.4511 |
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+ | 1.0803 | 1.2 | 2250 | 0.9891 | 0.6972 | 0.443 | 0.6383 | 0.6383 | 0.4479 |
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+ | 0.9849 | 1.33 | 2500 | 0.9800 | 0.7009 | 0.4467 | 0.6425 | 0.6425 | 0.4464 |
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+ | 0.9849 | 1.46 | 2750 | 0.9771 | 0.7017 | 0.4479 | 0.6426 | 0.6426 | 0.4437 |
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+ | 0.9867 | 1.6 | 3000 | 0.9638 | 0.7085 | 0.4541 | 0.6495 | 0.6495 | 0.4422 |
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+ | 0.9867 | 1.73 | 3250 | 0.9675 | 0.7013 | 0.4495 | 0.6438 | 0.6438 | 0.4413 |
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+ | 0.9556 | 1.86 | 3500 | 0.9565 | 0.707 | 0.4544 | 0.6493 | 0.6492 | 0.4401 |
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+ | 0.9556 | 1.99 | 3750 | 0.9558 | 0.7069 | 0.4544 | 0.6489 | 0.6489 | 0.4398 |
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  ### Framework versions
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