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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: retrieva-jp/bert-1.3b
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: out
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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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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/rspeech3399/huggingface/runs/zfb205ui)
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+ # out
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+
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+ This model is a fine-tuned version of [retrieva-jp/bert-1.3b](https://huggingface.co/retrieva-jp/bert-1.3b) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4714
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+ - Accuracy: 0.737
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+ - Precision: 0.7423
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+ - Recall: 0.726
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+ - F1: 0.7341
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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: 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_steps: 1000
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.6438 | 0.0080 | 100 | 0.6116 | 0.663 | 0.8721 | 0.382 | 0.5313 |
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+ | 0.5113 | 0.0160 | 200 | 0.5442 | 0.699 | 0.6736 | 0.772 | 0.7195 |
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+ | 0.4512 | 0.0240 | 300 | 0.5119 | 0.717 | 0.8359 | 0.54 | 0.6561 |
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+ | 0.3916 | 0.0321 | 400 | 0.4936 | 0.702 | 0.7295 | 0.642 | 0.6830 |
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+ | 0.3806 | 0.0401 | 500 | 0.4763 | 0.715 | 0.7708 | 0.612 | 0.6823 |
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+ | 0.3581 | 0.0481 | 600 | 0.4597 | 0.754 | 0.75 | 0.762 | 0.7560 |
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+ | 0.3308 | 0.0561 | 700 | 0.4690 | 0.742 | 0.7738 | 0.684 | 0.7261 |
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+ | 0.3458 | 0.0641 | 800 | 0.4703 | 0.737 | 0.7423 | 0.726 | 0.7341 |
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+ | 0.3475 | 0.0721 | 900 | 0.4728 | 0.737 | 0.7495 | 0.712 | 0.7303 |
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+ | 0.3435 | 0.0801 | 1000 | 0.4714 | 0.737 | 0.7423 | 0.726 | 0.7341 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.43.1
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ {
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+ "_name_or_path": "retrieva-jp/bert-1.3b",
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+ "RetrievaBertForSequenceClassification"
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+ ],
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+ "AutoConfig": "retrieva-jp/bert-1.3b--configuration_retrieva_bert.RetrievaBertConfig",
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+ "AutoModel": "retrieva-jp/bert-1.3b--modeling_retrieva_bert.RetrievaBertModel",
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+ "AutoModelForMultipleChoice": "retrieva-jp/bert-1.3b--modeling_retrieva_bert.RetrievaBertForMultipleChoice",
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+ "AutoModelForNextSentencePrediction": "retrieva-jp/bert-1.3b--modeling_retrieva_bert.RetrievaBertForNextSentencePrediction",
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+ "AutoModelForPreTraining": "retrieva-jp/bert-1.3b--modeling_retrieva_bert.RetrievaBertForPreTraining",
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+ "AutoModelForQuestionAnswering": "retrieva-jp/bert-1.3b--modeling_retrieva_bert.RetrievaBertForQuestionAnswering",
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+ "AutoModelForSequenceClassification": "retrieva-jp/bert-1.3b--modeling_retrieva_bert.RetrievaBertForSequenceClassification",
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+ "AutoModelForTokenClassification": "retrieva-jp/bert-1.3b--modeling_retrieva_bert.RetrievaBertForTokenClassification"
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+ },
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 1536,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 4096,
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+ "layer_norm_eps": 1e-12,
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+ "lm_head_hidden_act": "gelu",
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+ "max_position_embeddings": 2048,
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+ "mlp_bias": true,
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+ "num_attention_heads": 24,
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+ "num_hidden_layers": 48,
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+ "use_cache": true,
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