Model save
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README.md
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---
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license: mit
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base_model: intfloat/multilingual-e5-large
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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: miner-24_e5
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results: []
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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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# miner-24_e5
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This model is a fine-tuned version of [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8934
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- Accuracy: 0.796
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- Ball: 0.125
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- Precision: 0.0995
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- Recall: 0.125
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- F1: 0.1108
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 8
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- eval_batch_size: 8
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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
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Ball | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:---------:|:------:|:------:|
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| 1.4223 | 1.0 | 624 | 0.8490 | 0.796 | 0.125 | 0.0995 | 0.125 | 0.1108 |
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| 1.3854 | 2.0 | 1248 | 0.8556 | 0.796 | 0.125 | 0.0995 | 0.125 | 0.1108 |
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| 1.3709 | 3.0 | 1872 | 0.8934 | 0.796 | 0.125 | 0.0995 | 0.125 | 0.1108 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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model.safetensors
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runs/Jun19_06-33-36_9092d547618f/events.out.tfevents.1718778818.9092d547618f.3124.1
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