bge-small-en-v1.5-2024-12-06_14-23-52

README.md

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+---
+library_name: transformers
+license: mit
+base_model: BAAI/bge-small-en-v1.5
+tags:
+- generated_from_trainer
+model-index:
+- name: bge-small-en-v1.5-2024-12-06_14-23-52-relevancy-1
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# bge-small-en-v1.5-2024-12-06_14-23-52-relevancy-1
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.0219
+- Spearman: 0.9313
+- Pearson: 0.9323
+- Mse: 0.0219
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 64
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 256
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.05
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Spearman | Pearson | Mse    |
+|:-------------:|:------:|:-----:|:---------------:|:--------:|:-------:|:------:|
+| 0.0334        | 0.3998 | 1055  | 0.0291          | 0.9039   | 0.9070  | 0.0291 |
+| 0.0276        | 0.7997 | 2110  | 0.0264          | 0.9129   | 0.9165  | 0.0264 |
+| 0.0244        | 1.1995 | 3165  | 0.0253          | 0.9185   | 0.9215  | 0.0253 |
+| 0.0239        | 1.5994 | 4220  | 0.0230          | 0.9235   | 0.9271  | 0.0230 |
+| 0.0217        | 1.9992 | 5275  | 0.0234          | 0.9252   | 0.9294  | 0.0234 |
+| 0.0186        | 2.3991 | 6330  | 0.0228          | 0.9272   | 0.9304  | 0.0228 |
+| 0.0174        | 2.7989 | 7385  | 0.0219          | 0.9286   | 0.9320  | 0.0219 |
+| 0.0136        | 3.1988 | 8440  | 0.0221          | 0.9290   | 0.9314  | 0.0221 |
+| 0.014         | 3.5986 | 9495  | 0.0218          | 0.9304   | 0.9329  | 0.0218 |
+| 0.0149        | 3.9985 | 10550 | 0.0215          | 0.9305   | 0.9332  | 0.0215 |
+| 0.0112        | 4.3983 | 11605 | 0.0217          | 0.9305   | 0.9332  | 0.0217 |
+| 0.0127        | 4.7982 | 12660 | 0.0217          | 0.9306   | 0.9333  | 0.0217 |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.4.1+cu121
+- Datasets 2.19.2
+- Tokenizers 0.20.3

config.json

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+{
+  "_name_or_path": "BAAI/bge-small-en-v1.5",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 384,
+  "id2label": {
+    "0": "LABEL_0"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 1536,
+  "label2id": {
+    "LABEL_0": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "regression",
+  "torch_dtype": "float32",
+  "transformers_version": "4.46.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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+size 133464836

training_args.bin

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