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Demosthene-OR
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t5-base-finetuned-en-to-fr

Translation
Transformers
PyTorch
English
French
t5
text2text-generation
Generated from Trainer
text-generation-inference
Inference Endpoints
Model card Files Community
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Demosthene-OR commited on
Commit
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End of training

Browse files
Files changed (9) hide show
  1. README.md +160 -0
  2. config.json +61 -0
  3. generation_config.json +6 -0
  4. pytorch_model.bin +3 -0
  5. special_tokens_map.json +107 -0
  6. spiece.model +3 -0
  7. tokenizer.json +0 -0
  8. tokenizer_config.json +111 -0
  9. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: t5-base
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - bleu
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+ model-index:
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+ - name: t5-base-finetuned-en-to-fr
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # t5-base-finetuned-en-to-fr
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+
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+ This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0007
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+ - Bleu: 100.0
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+ - Gen Len: 7.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-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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+ - num_epochs: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
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+ | No log | 1.0 | 1 | 0.1580 | 88.3831 | 7.4545 |
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+ | No log | 2.0 | 2 | 0.1440 | 88.3831 | 7.2727 |
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+ | No log | 3.0 | 3 | 0.1307 | 89.8848 | 7.4545 |
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+ | No log | 4.0 | 4 | 0.1188 | 89.8848 | 7.4545 |
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+ | No log | 5.0 | 5 | 0.1077 | 89.8848 | 7.4545 |
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+ | No log | 6.0 | 6 | 0.0978 | 94.6403 | 7.2727 |
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+ | No log | 7.0 | 7 | 0.0886 | 99.3527 | 7.1818 |
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+ | No log | 8.0 | 8 | 0.0799 | 99.3527 | 7.1818 |
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+ | No log | 9.0 | 9 | 0.0718 | 100.0 | 7.0 |
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+ | No log | 10.0 | 10 | 0.0641 | 100.0 | 7.0 |
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+ | No log | 11.0 | 11 | 0.0571 | 100.0 | 7.0 |
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+ | No log | 12.0 | 12 | 0.0506 | 100.0 | 7.0 |
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+ | No log | 13.0 | 13 | 0.0447 | 100.0 | 7.0 |
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+ | No log | 14.0 | 14 | 0.0394 | 100.0 | 7.0 |
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+ | No log | 15.0 | 15 | 0.0347 | 100.0 | 7.0 |
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+ | No log | 16.0 | 16 | 0.0304 | 100.0 | 7.0 |
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+ | No log | 17.0 | 17 | 0.0266 | 100.0 | 7.0 |
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+ | No log | 18.0 | 18 | 0.0231 | 100.0 | 7.0 |
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+ | No log | 19.0 | 19 | 0.0202 | 100.0 | 7.0 |
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+ | No log | 20.0 | 20 | 0.0175 | 100.0 | 7.0 |
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+ | No log | 21.0 | 21 | 0.0152 | 100.0 | 7.0 |
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+ | No log | 22.0 | 22 | 0.0133 | 100.0 | 7.0 |
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+ | No log | 23.0 | 23 | 0.0116 | 100.0 | 7.0 |
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+ | No log | 24.0 | 24 | 0.0103 | 100.0 | 7.0 |
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+ | No log | 25.0 | 25 | 0.0091 | 100.0 | 7.0 |
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+ | No log | 26.0 | 26 | 0.0080 | 100.0 | 7.0 |
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+ | No log | 27.0 | 27 | 0.0071 | 100.0 | 7.0 |
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+ | No log | 28.0 | 28 | 0.0064 | 100.0 | 7.0 |
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+ | No log | 29.0 | 29 | 0.0057 | 100.0 | 7.0 |
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+ | No log | 30.0 | 30 | 0.0052 | 100.0 | 7.0 |
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+ | No log | 31.0 | 31 | 0.0047 | 100.0 | 7.0 |
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+ | No log | 32.0 | 32 | 0.0043 | 100.0 | 7.0 |
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+ | No log | 33.0 | 33 | 0.0039 | 100.0 | 7.0 |
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+ | No log | 34.0 | 34 | 0.0035 | 100.0 | 7.0 |
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+ | No log | 35.0 | 35 | 0.0032 | 100.0 | 7.0 |
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+ | No log | 36.0 | 36 | 0.0030 | 100.0 | 7.0 |
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+ | No log | 37.0 | 37 | 0.0028 | 100.0 | 7.0 |
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+ | No log | 38.0 | 38 | 0.0025 | 100.0 | 7.0 |
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+ | No log | 39.0 | 39 | 0.0024 | 100.0 | 7.0 |
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+ | No log | 40.0 | 40 | 0.0022 | 100.0 | 7.0 |
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+ | No log | 41.0 | 41 | 0.0021 | 100.0 | 7.0 |
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+ | No log | 42.0 | 42 | 0.0020 | 100.0 | 7.0 |
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+ | No log | 43.0 | 43 | 0.0019 | 100.0 | 7.0 |
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+ | No log | 44.0 | 44 | 0.0018 | 100.0 | 7.0 |
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+ | No log | 45.0 | 45 | 0.0017 | 100.0 | 7.0 |
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+ | No log | 46.0 | 46 | 0.0016 | 100.0 | 7.0 |
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+ | No log | 47.0 | 47 | 0.0015 | 100.0 | 7.0 |
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+ | No log | 48.0 | 48 | 0.0015 | 100.0 | 7.0 |
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+ | No log | 49.0 | 49 | 0.0014 | 100.0 | 7.0 |
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+ | No log | 50.0 | 50 | 0.0013 | 100.0 | 7.0 |
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+ | No log | 51.0 | 51 | 0.0013 | 100.0 | 7.0 |
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+ | No log | 52.0 | 52 | 0.0013 | 100.0 | 7.0 |
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+ | No log | 53.0 | 53 | 0.0012 | 100.0 | 7.0 |
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+ | No log | 54.0 | 54 | 0.0012 | 100.0 | 7.0 |
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+ | No log | 55.0 | 55 | 0.0011 | 100.0 | 7.0 |
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+ | No log | 56.0 | 56 | 0.0011 | 100.0 | 7.0 |
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+ | No log | 57.0 | 57 | 0.0011 | 100.0 | 7.0 |
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+ | No log | 58.0 | 58 | 0.0011 | 100.0 | 7.0 |
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+ | No log | 59.0 | 59 | 0.0011 | 100.0 | 7.0 |
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+ | No log | 60.0 | 60 | 0.0010 | 100.0 | 7.0 |
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+ | No log | 61.0 | 61 | 0.0010 | 100.0 | 7.0 |
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+ | No log | 62.0 | 62 | 0.0010 | 100.0 | 7.0 |
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+ | No log | 63.0 | 63 | 0.0010 | 100.0 | 7.0 |
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+ | No log | 64.0 | 64 | 0.0010 | 100.0 | 7.0 |
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+ | No log | 65.0 | 65 | 0.0009 | 100.0 | 7.0 |
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+ | No log | 66.0 | 66 | 0.0009 | 100.0 | 7.0 |
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+ | No log | 67.0 | 67 | 0.0009 | 100.0 | 7.0 |
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+ | No log | 68.0 | 68 | 0.0009 | 100.0 | 7.0 |
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+ | No log | 69.0 | 69 | 0.0009 | 100.0 | 7.0 |
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+ | No log | 70.0 | 70 | 0.0009 | 100.0 | 7.0 |
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+ | No log | 71.0 | 71 | 0.0009 | 100.0 | 7.0 |
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+ | No log | 72.0 | 72 | 0.0009 | 100.0 | 7.0 |
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+ | No log | 73.0 | 73 | 0.0009 | 100.0 | 7.0 |
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+ | No log | 74.0 | 74 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 75.0 | 75 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 76.0 | 76 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 77.0 | 77 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 78.0 | 78 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 79.0 | 79 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 80.0 | 80 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 81.0 | 81 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 82.0 | 82 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 83.0 | 83 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 84.0 | 84 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 85.0 | 85 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 86.0 | 86 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 87.0 | 87 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 88.0 | 88 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 89.0 | 89 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 90.0 | 90 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 91.0 | 91 | 0.0008 | 100.0 | 7.0 |
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+ | No log | 92.0 | 92 | 0.0007 | 100.0 | 7.0 |
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+ | No log | 93.0 | 93 | 0.0007 | 100.0 | 7.0 |
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+ | No log | 94.0 | 94 | 0.0007 | 100.0 | 7.0 |
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+ | No log | 95.0 | 95 | 0.0007 | 100.0 | 7.0 |
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+ | No log | 96.0 | 96 | 0.0007 | 100.0 | 7.0 |
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+ | No log | 97.0 | 97 | 0.0007 | 100.0 | 7.0 |
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+ | No log | 98.0 | 98 | 0.0007 | 100.0 | 7.0 |
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+ | No log | 99.0 | 99 | 0.0007 | 100.0 | 7.0 |
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+ | No log | 100.0 | 100 | 0.0007 | 100.0 | 7.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.1
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+ - Pytorch 2.0.1
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+ - Datasets 2.13.0
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+ - Tokenizers 0.13.2
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+ "translation_en_to_de": {
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+ "early_stopping": true,
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+ "max_length": 300,
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+ "num_beams": 4,
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+ "prefix": "translate English to German: "
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+ "translation_en_to_fr": {
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+ "early_stopping": true,
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+ "max_length": 300,
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+ "num_beams": 4,
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+ "prefix": "translate English to French: "
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+ "translation_en_to_ro": {
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+ "prefix": "translate English to Romanian: "
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