End of training

README.md

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+---
+library_name: transformers
+license: cc-by-nc-sa-4.0
+base_model: InstaDeepAI/nucleotide-transformer-2.5b-1000g
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- accuracy
+model-index:
+- name: nucleotide-transformer-2.5b-1000g_ft_BioS74_1kbpHG19_DHSs_H3K27AC_one_shot
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# nucleotide-transformer-2.5b-1000g_ft_BioS74_1kbpHG19_DHSs_H3K27AC_one_shot
+
+This model is a fine-tuned version of [InstaDeepAI/nucleotide-transformer-2.5b-1000g](https://huggingface.co/InstaDeepAI/nucleotide-transformer-2.5b-1000g) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.8588
+- F1 Score: 0.8095
+- Precision: 0.7727
+- Recall: 0.85
+- Accuracy: 0.7895
+- Auc: 0.8694
+- Prc: 0.8861
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | F1 Score | Precision | Recall | Accuracy | Auc    | Prc    |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|:------:|:------:|
+| 0.0931        | 13.1579 | 500  | 1.8588          | 0.8095   | 0.7727    | 0.85   | 0.7895   | 0.8694 | 0.8861 |
+
+
+### Framework versions
+
+- Transformers 4.46.0.dev0
+- Pytorch 2.4.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.20.0

config.json

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+  "hidden_size": 2560,
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+  "intermediate_size": 10240,
+  "is_folding_model": false,
+  "layer_norm_eps": 1e-12,
+  "mask_token_id": 2,
+  "max_position_embeddings": 1002,
+  "model_type": "esm",
+  "num_attention_heads": 20,
+  "num_hidden_layers": 32,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "tie_word_embeddings": false,
+  "token_dropout": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.46.0.dev0",
+  "use_cache": false,
+  "use_flash_attention": false,
+  "vocab_list": null,
+  "vocab_size": 4105
+}

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special_tokens_map.json

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tokenizer_config.json

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+CCTGTC
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+CGTGAA
+CGTGAT
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+CGTGTA
+CGTGTT
+CGTGTC
+CGTGTG
+CGTGCA
+CGTGCT
+CGTGCC
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+CGTGGC
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+CGCGTT
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+CGCGCA
+CGCGCT
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+CGCGGT
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+CGGAAA
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+CGGTTT
+CGGTTC
+CGGTTG
+CGGTCA
+CGGTCT
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+CGGTGA
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+CGGTGC
+CGGTGG
+CGGCAA
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+CGGCTT
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+CGGCCA
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+CGGGAT
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+CGGGTA
+CGGGTT
+CGGGTC
+CGGGTG
+CGGGCA
+CGGGCT
+CGGGCC
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+CGGGGT
+CGGGGC
+CGGGGG
+GAAAAA
+GAAAAT
+GAAAAC
+GAAAAG
+GAAATA
+GAAATT
+GAAATC
+GAAATG
+GAAACA
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+GAAAGA
+GAAAGT
+GAAAGC
+GAAAGG
+GAATAA
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+GAATGG
+GAACAA
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+GAACCC
+GAACCG
+GAACGA
+GAACGT
+GAACGC
+GAACGG
+GAAGAA
+GAAGAT
+GAAGAC
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+GAAGTA
+GAAGTT
+GAAGTC
+GAAGTG
+GAAGCA
+GAAGCT
+GAAGCC
+GAAGCG
+GAAGGA
+GAAGGT
+GAAGGC
+GAAGGG
+GATAAA
+GATAAT
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+GATAAG
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+GATATC
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+GATTGG
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+GATGCT
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+GATGGT
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+GACAAA
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+GACAGG
+GACTAA
+GACTAT
+GACTAC
+GACTAG
+GACTTA
+GACTTT
+GACTTC
+GACTTG
+GACTCA
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+<eos>
+<bos>