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Text2Text Generation
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Safetensors
m2m_100
Generated from Trainer
Inference Endpoints
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the one with .165

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  1. README.md +13 -13
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1841
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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- - train_batch_size: 8
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- - eval_batch_size: 8
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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
@@ -46,16 +46,16 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 3.8401 | 0.11 | 100 | 0.4579 |
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- | 0.3757 | 0.23 | 200 | 0.2560 |
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- | 0.2783 | 0.34 | 300 | 0.2298 |
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- | 0.2618 | 0.46 | 400 | 0.2190 |
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- | 0.2733 | 0.57 | 500 | 0.2061 |
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- | 0.2236 | 0.69 | 600 | 0.2001 |
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- | 0.2183 | 0.8 | 700 | 0.1939 |
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- | 0.2315 | 0.91 | 800 | 0.1875 |
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- | 0.2058 | 1.03 | 900 | 0.1848 |
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- | 0.1705 | 1.14 | 1000 | 0.1841 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1653
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 5e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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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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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 3.8064 | 0.2 | 100 | 0.4321 |
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+ | 0.3145 | 0.41 | 200 | 0.2218 |
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+ | 0.2633 | 0.61 | 300 | 0.1970 |
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+ | 0.2428 | 0.81 | 400 | 0.1871 |
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+ | 0.2162 | 1.02 | 500 | 0.1786 |
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+ | 0.163 | 1.22 | 600 | 0.1744 |
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+ | 0.1515 | 1.42 | 700 | 0.1713 |
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+ | 0.1423 | 1.63 | 800 | 0.1696 |
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+ | 0.1439 | 1.83 | 900 | 0.1660 |
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+ | 0.1484 | 2.03 | 1000 | 0.1653 |
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  ### Framework versions
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