tydymy/nucleotide-transformer-500m-1000g-finetuned-human-150bp-dna-classification
Browse files- README.md +68 -0
- config.json +30 -0
- model.safetensors +3 -0
- training_args.bin +3 -0
README.md
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---
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license: cc-by-nc-sa-4.0
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base_model: InstaDeepAI/nucleotide-transformer-500m-1000g
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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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- f1
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- precision
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- recall
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model-index:
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- name: nucleotide-transformer-500m-1000g-finetuned-human-150bp-dna-classification
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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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# nucleotide-transformer-500m-1000g-finetuned-human-150bp-dna-classification
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This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-500m-1000g](https://huggingface.co/InstaDeepAI/nucleotide-transformer-500m-1000g) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2793
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- Accuracy: 0.9411
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- F1: 0.9411
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- Precision: 0.9377
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- Recall: 0.9445
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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: 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: 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 | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.229 | 1.0 | 3125 | 0.2042 | 0.9187 | 0.9203 | 0.8977 | 0.9440 |
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| 0.2019 | 2.0 | 6250 | 0.2176 | 0.9360 | 0.9340 | 0.9590 | 0.9102 |
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| 0.0008 | 3.0 | 9375 | 0.2958 | 0.9397 | 0.9395 | 0.9371 | 0.9420 |
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### Framework versions
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- Transformers 4.35.0
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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config.json
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{
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"_name_or_path": "InstaDeepAI/nucleotide-transformer-500m-1000g",
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"architectures": [
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"EsmForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"emb_layer_norm_before": false,
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"esmfold_config": null,
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"hidden_dropout_prob": 0.0,
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"hidden_size": 1280,
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"initializer_range": 0.02,
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"intermediate_size": 5120,
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"is_folding_model": false,
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"layer_norm_eps": 1e-12,
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"mask_token_id": 2,
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"max_position_embeddings": 1002,
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"model_type": "esm",
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"num_attention_heads": 20,
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"num_hidden_layers": 24,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"tie_word_embeddings": false,
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"token_dropout": true,
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"torch_dtype": "float32",
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"transformers_version": "4.35.0",
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"use_cache": false,
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"vocab_list": null,
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"vocab_size": 4105
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:313d1f6b0b265cfc4ebc9b76c83a5400dc4bbf9829e663ebe87582f772d56507
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size 1921809396
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:84c19d5f70a9e97e91617c13ef7a386737c53d30309848f563258294b751e851
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size 4600
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