Model save
Browse files- README.md +69 -0
- logs/events.out.tfevents.1745372447.s_005_m.2850345.156 +2 -2
- model.safetensors +1 -1
README.md
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---
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library_name: transformers
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base_model: Hartunka/distilbert_rand_50_v2
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tags:
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- generated_from_trainer
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metrics:
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- spearmanr
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model-index:
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- name: distilbert_rand_50_v2_stsb
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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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# distilbert_rand_50_v2_stsb
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This model is a fine-tuned version of [Hartunka/distilbert_rand_50_v2](https://huggingface.co/Hartunka/distilbert_rand_50_v2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.6337
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- Pearson: 0.2887
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- Spearmanr: 0.2803
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- Combined Score: 0.2845
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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: 5e-05
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- train_batch_size: 256
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- eval_batch_size: 256
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- seed: 10
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- optimizer: Use 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: linear
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- num_epochs: 50
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:|
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| 3.0153 | 1.0 | 23 | 2.4353 | 0.1203 | 0.1031 | 0.1117 |
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| 1.9567 | 2.0 | 46 | 2.4981 | 0.1854 | 0.1692 | 0.1773 |
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| 1.7232 | 3.0 | 69 | 2.2659 | 0.2493 | 0.2367 | 0.2430 |
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| 1.4358 | 4.0 | 92 | 2.2973 | 0.2887 | 0.2818 | 0.2852 |
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| 1.0785 | 5.0 | 115 | 2.6259 | 0.2453 | 0.2340 | 0.2396 |
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| 0.7743 | 6.0 | 138 | 2.5245 | 0.2873 | 0.2825 | 0.2849 |
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| 0.5991 | 7.0 | 161 | 2.6255 | 0.3081 | 0.3047 | 0.3064 |
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| 0.479 | 8.0 | 184 | 2.6337 | 0.2887 | 0.2803 | 0.2845 |
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### Framework versions
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- Transformers 4.50.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.21.1
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