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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/mt5-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: mt5-base-finetuned-en-to-tr-colab
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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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+ # mt5-base-finetuned-en-to-tr-colab
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+
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+ This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: nan
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+ - Bleu: 0.0851
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+ - Gen Len: 7.1921
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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: 3
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+ - mixed_precision_training: Native AMP
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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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+ | 0.0 | 1.0 | 12851 | nan | 0.0851 | 7.1921 |
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+ | 0.0 | 2.0 | 25702 | nan | 0.0851 | 7.1921 |
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+ | 0.0 | 3.0 | 38553 | nan | 0.0851 | 7.1921 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.1
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+ - Pytorch 2.2.1
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.1
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+ ],
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+ "dense_act_fn": "gelu_new",
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+ "layer_norm_epsilon": 1e-06,
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+ "num_decoder_layers": 12,
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+ "num_heads": 12,
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+ "output_past": true,
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+ "relative_attention_max_distance": 128,
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+ "relative_attention_num_buckets": 32,
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+ "tie_word_embeddings": false,
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+ "tokenizer_class": "T5Tokenizer",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.39.1",
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+ "use_cache": true,
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+ "vocab_size": 250112
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+ }
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