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bge-small-en-v1.5-2024-12-07_11-40-21

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  1. README.md +75 -0
  2. config.json +32 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: BAAI/bge-small-en-v1.5
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: bge-small-en-v1.5-2024-12-07_11-40-21-quality-weight-0.3
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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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+ # bge-small-en-v1.5-2024-12-07_11-40-21-quality-weight-0.3
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+
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+ This model is a fine-tuned version of [BAAI/bge-small-en-v1.5](https://huggingface.co/BAAI/bge-small-en-v1.5) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0204
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+ - Spearman: 0.9287
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+ - Pearson: 0.9299
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+ - Mse: 0.0204
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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: 64
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 256
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.05
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+ - num_epochs: 5
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Spearman | Pearson | Mse |
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+ |:-------------:|:------:|:-----:|:---------------:|:--------:|:-------:|:------:|
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+ | 0.0308 | 0.3998 | 1055 | 0.0270 | 0.9002 | 0.9029 | 0.0270 |
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+ | 0.026 | 0.7997 | 2110 | 0.0243 | 0.9100 | 0.9139 | 0.0243 |
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+ | 0.0226 | 1.1995 | 3165 | 0.0237 | 0.9153 | 0.9187 | 0.0237 |
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+ | 0.0222 | 1.5994 | 4220 | 0.0214 | 0.9218 | 0.9243 | 0.0214 |
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+ | 0.0202 | 1.9992 | 5275 | 0.0217 | 0.9228 | 0.9265 | 0.0217 |
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+ | 0.0175 | 2.3991 | 6330 | 0.0209 | 0.9235 | 0.9282 | 0.0209 |
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+ | 0.0163 | 2.7989 | 7385 | 0.0202 | 0.9258 | 0.9299 | 0.0202 |
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+ | 0.0127 | 3.1988 | 8440 | 0.0204 | 0.9268 | 0.9291 | 0.0204 |
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+ | 0.0137 | 3.5986 | 9495 | 0.0201 | 0.9279 | 0.9308 | 0.0201 |
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+ | 0.0142 | 3.9985 | 10550 | 0.0199 | 0.9278 | 0.9310 | 0.0199 |
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+ | 0.0106 | 4.3983 | 11605 | 0.0202 | 0.9280 | 0.9309 | 0.0202 |
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+ | 0.012 | 4.7982 | 12660 | 0.0202 | 0.9282 | 0.9310 | 0.0202 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.3
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 2.19.2
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+ - Tokenizers 0.20.3
config.json ADDED
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+ {
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+ "_name_or_path": "BAAI/bge-small-en-v1.5",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 384,
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+ "id2label": {
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+ "0": "LABEL_0"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 1536,
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+ "LABEL_0": 0
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "regression",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.46.3",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30522
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+ }
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