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pjbhaumik/km-cross-encoder2

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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: cross-encoder/ms-marco-MiniLM-L-6-v2
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: crossencoder-km1
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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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+ # crossencoder-km1
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+
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+ This model is a fine-tuned version of [cross-encoder/ms-marco-MiniLM-L-6-v2](https://huggingface.co/cross-encoder/ms-marco-MiniLM-L-6-v2) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0889
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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: 80
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+ - eval_batch_size: 80
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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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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 10
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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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+ | 99.5928 | 1.0 | 13 | 102.9756 |
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+ | 98.0949 | 2.0 | 26 | 99.8849 |
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+ | 95.3147 | 3.0 | 39 | 92.5186 |
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+ | 76.7659 | 4.0 | 52 | 69.9192 |
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+ | 54.0033 | 5.0 | 65 | 21.3535 |
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+ | 20.7192 | 6.0 | 78 | 7.2049 |
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+ | 3.2855 | 7.0 | 91 | 2.0372 |
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+ | 0.9629 | 8.0 | 104 | 0.3949 |
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+ | 0.4633 | 9.0 | 117 | 0.1386 |
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+ | 0.2156 | 10.0 | 130 | 0.0975 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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+ - Pytorch 2.0.1
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+ - Datasets 2.17.0
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+ - Tokenizers 0.15.2
config.json ADDED
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+ "layer_norm_eps": 1e-12,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 6,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "regression",
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+ "sbert_ce_default_activation_function": "torch.nn.modules.linear.Identity",
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+ "torch_dtype": "float32",
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+ "type_vocab_size": 2,
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+ }
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