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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: thenlper/gte-base
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: gte-base-finetuned-imdb
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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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+ # gte-base-finetuned-imdb
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+
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+ This model is a fine-tuned version of [thenlper/gte-base](https://huggingface.co/thenlper/gte-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 7.3837
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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: 32
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+ - eval_batch_size: 32
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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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+ - num_epochs: 3.0
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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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+ | 8.9078 | 1.0 | 32 | 7.6809 |
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+ | 7.555 | 2.0 | 64 | 7.4141 |
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+ | 7.4182 | 3.0 | 96 | 7.3361 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0
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+ - Pytorch 2.1.0
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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+ {
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+ "BertForMaskedLM"
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+ ],
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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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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+ "torch_dtype": "float32",
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+ "transformers_version": "4.35.0",
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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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