End of training
Browse files- README.md +73 -0
- adapter_config.json +33 -0
- adapter_model.safetensors +3 -0
- training_args.bin +3 -0
README.md
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---
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license: mit
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library_name: peft
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tags:
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- generated_from_trainer
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base_model: facebook/esm2_t12_35M_UR50D
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metrics:
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- precision
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- recall
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- accuracy
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model-index:
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- name: esm2-t12-35M-lora-64-remote-homology-filtered
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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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# esm2-t12-35M-lora-64-remote-homology-filtered
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This model is a fine-tuned version of [facebook/esm2_t12_35M_UR50D](https://huggingface.co/facebook/esm2_t12_35M_UR50D) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5657
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- Precision: 0.7166
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- Recall: 0.6986
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- F1-score: 0.7075
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- Accuracy: 0.7141
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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: 3e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 5
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1-score | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:--------:|:--------:|
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| 0.6191 | 1.0 | 7969 | 0.6185 | 0.6919 | 0.5824 | 0.6325 | 0.6650 |
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| 0.5921 | 2.0 | 15938 | 0.5838 | 0.7201 | 0.6339 | 0.6742 | 0.6968 |
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| 0.5874 | 3.0 | 23907 | 0.5751 | 0.7439 | 0.6104 | 0.6705 | 0.7032 |
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| 0.5593 | 4.0 | 31876 | 0.5664 | 0.7210 | 0.6833 | 0.7016 | 0.7124 |
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| 0.576 | 5.0 | 39845 | 0.5657 | 0.7166 | 0.6986 | 0.7075 | 0.7141 |
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### Framework versions
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- PEFT 0.11.1
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- Transformers 4.39.3
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- Pytorch 2.1.2
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "facebook/esm2_t12_35M_UR50D",
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"bias": "all",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 128,
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"lora_dropout": 0.1,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": [
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"classifier",
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"score"
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],
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"peft_type": "LORA",
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"r": 64,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"query",
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"value",
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"key"
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],
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"task_type": "SEQ_CLS",
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"use_dora": false,
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"use_rslora": false
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}
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:f2c3a0122e6108bd964ac7007d143e737e0cd762c3dd908ba4bb90ebfac5834e
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size 10057596
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:d09122c40de9b78814f941ea0bc441baa5e9235fdfe65bfbc4fed9ef4d5ce254
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size 4984
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