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End of training

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README.md ADDED
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+ ---
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+ base_model: facebook/mbart-large-50-many-to-many-mmt
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: hanzi_huayu_translation
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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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+ # hanzi_huayu_translation
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+
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+ This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2578
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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: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 16
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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 |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 0.7672 | 1.0 | 948 | 0.2927 |
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+ | 0.2853 | 2.0 | 1897 | 0.2656 |
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+ | 0.2469 | 3.0 | 2844 | 0.2578 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.1.2
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+ - Datasets 2.1.0
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+ - Tokenizers 0.15.2
config.json ADDED
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+ {
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+ "_name_or_path": "facebook/mbart-large-50-many-to-many-mmt",
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+ "_num_labels": 3,
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+ "activation_dropout": 0.0,
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+ "activation_function": "relu",
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+ "add_bias_logits": false,
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+ "add_final_layer_norm": true,
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+ "architectures": [
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+ "MBartForConditionalGeneration"
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+ ],
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 0,
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+ "classif_dropout": 0.0,
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+ "classifier_dropout": 0.0,
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+ "d_model": 1024,
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+ "decoder_attention_heads": 16,
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+ "decoder_ffn_dim": 4096,
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+ "decoder_layerdrop": 0.0,
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+ "decoder_layers": 12,
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+ "decoder_start_token_id": 2,
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+ "dropout": 0.1,
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+ "early_stopping": true,
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+ "encoder_attention_heads": 16,
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+ "encoder_ffn_dim": 4096,
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+ "encoder_layerdrop": 0.0,
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+ "encoder_layers": 12,
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+ "eos_token_id": 2,
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+ "forced_eos_token_id": 2,
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+ "gradient_checkpointing": false,
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+ "id2label": {
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+ "0": "LABEL_0",
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+ "1": "LABEL_1",
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+ "2": "LABEL_2"
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+ },
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+ "init_std": 0.02,
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+ "is_encoder_decoder": true,
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+ "label2id": {
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+ "LABEL_1": 1,
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+ "LABEL_2": 2
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+ },
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+ "max_length": 200,
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+ "max_position_embeddings": 1024,
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+ "model_type": "mbart",
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+ "normalize_before": true,
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+ "normalize_embedding": true,
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+ "num_beams": 5,
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+ "num_hidden_layers": 12,
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+ "output_past": true,
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+ "pad_token_id": 1,
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+ "scale_embedding": true,
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+ "static_position_embeddings": false,
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+ "tokenizer_class": "MBart50Tokenizer",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.38.2",
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+ "use_cache": true,
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+ "vocab_size": 250054
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+ }
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+ "max_length": 200,
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+ "num_beams": 5,
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+ "pad_token_id": 1,
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+ "transformers_version": "4.38.2"
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+ }
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