End of training

README.md

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+---
+base_model: AIRI-Institute/gena-lm-bert-base-t2t-multi
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- accuracy
+model-index:
+- name: gena-lm-bert-base-t2t-multi_ft_BioS73_1kbpHG19_DHSs_H3K27AC
+  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. -->
+
+# gena-lm-bert-base-t2t-multi_ft_BioS73_1kbpHG19_DHSs_H3K27AC
+
+This model is a fine-tuned version of [AIRI-Institute/gena-lm-bert-base-t2t-multi](https://huggingface.co/AIRI-Institute/gena-lm-bert-base-t2t-multi) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5503
+- F1 Score: 0.8650
+- Precision: 0.8391
+- Recall: 0.8925
+- Accuracy: 0.8513
+- Auc: 0.8910
+- Prc: 0.8501
+
+## 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    |
+|:-------------:|:------:|:-----:|:---------------:|:--------:|:---------:|:------:|:--------:|:------:|:------:|
+| 0.6862        | 0.1864 | 500   | 0.6364          | 0.7934   | 0.7511    | 0.8408 | 0.7663   | 0.8211 | 0.8070 |
+| 0.6114        | 0.3727 | 1000  | 0.5230          | 0.8189   | 0.7812    | 0.8603 | 0.7969   | 0.8235 | 0.7910 |
+| 0.4843        | 0.5591 | 1500  | 0.4601          | 0.8377   | 0.7866    | 0.8959 | 0.8148   | 0.8793 | 0.8586 |
+| 0.4567        | 0.7454 | 2000  | 0.4643          | 0.8374   | 0.8181    | 0.8575 | 0.8222   | 0.8875 | 0.8761 |
+| 0.4294        | 0.9318 | 2500  | 0.4666          | 0.8468   | 0.8109    | 0.8862 | 0.8289   | 0.8878 | 0.8750 |
+| 0.4283        | 1.1182 | 3000  | 0.4356          | 0.8457   | 0.8238    | 0.8687 | 0.8308   | 0.8982 | 0.8833 |
+| 0.4067        | 1.3045 | 3500  | 0.4572          | 0.8411   | 0.8429    | 0.8394 | 0.8308   | 0.9020 | 0.8824 |
+| 0.4167        | 1.4909 | 4000  | 0.4264          | 0.8464   | 0.8259    | 0.8680 | 0.8319   | 0.9039 | 0.8820 |
+| 0.3906        | 1.6772 | 4500  | 0.4686          | 0.8525   | 0.8214    | 0.8862 | 0.8364   | 0.8748 | 0.8126 |
+| 0.4078        | 1.8636 | 5000  | 0.4441          | 0.8515   | 0.8056    | 0.9029 | 0.8319   | 0.9010 | 0.8761 |
+| 0.3771        | 2.0499 | 5500  | 0.5151          | 0.8503   | 0.8275    | 0.8743 | 0.8356   | 0.9025 | 0.8766 |
+| 0.4282        | 2.2363 | 6000  | 0.5186          | 0.8528   | 0.8102    | 0.9001 | 0.8341   | 0.9065 | 0.8938 |
+| 0.4063        | 2.4227 | 6500  | 0.4397          | 0.8540   | 0.8291    | 0.8806 | 0.8394   | 0.9048 | 0.8749 |
+| 0.3998        | 2.6090 | 7000  | 0.4794          | 0.8585   | 0.8350    | 0.8834 | 0.8446   | 0.9008 | 0.8643 |
+| 0.3783        | 2.7954 | 7500  | 0.5577          | 0.8473   | 0.8577    | 0.8373 | 0.8390   | 0.9061 | 0.8827 |
+| 0.3926        | 2.9817 | 8000  | 0.4794          | 0.8618   | 0.8313    | 0.8946 | 0.8468   | 0.8907 | 0.8481 |
+| 0.4023        | 3.1681 | 8500  | 0.5062          | 0.8583   | 0.7932    | 0.9351 | 0.8353   | 0.9041 | 0.8888 |
+| 0.382         | 3.3545 | 9000  | 0.5005          | 0.8604   | 0.8193    | 0.9057 | 0.8431   | 0.9086 | 0.8838 |
+| 0.407         | 3.5408 | 9500  | 0.5177          | 0.8591   | 0.8399    | 0.8792 | 0.8461   | 0.9087 | 0.8901 |
+| 0.3773        | 3.7272 | 10000 | 0.5228          | 0.8654   | 0.8388    | 0.8939 | 0.8517   | 0.9043 | 0.8743 |
+| 0.392         | 3.9135 | 10500 | 0.5146          | 0.8649   | 0.8354    | 0.8966 | 0.8505   | 0.8937 | 0.8569 |
+| 0.3817        | 4.0999 | 11000 | 0.5353          | 0.8643   | 0.8146    | 0.9204 | 0.8457   | 0.8642 | 0.8163 |
+| 0.4062        | 4.2862 | 11500 | 0.5992          | 0.8472   | 0.8732    | 0.8226 | 0.8416   | 0.9122 | 0.8882 |
+| 0.3737        | 4.4726 | 12000 | 0.5634          | 0.8645   | 0.8245    | 0.9085 | 0.8479   | 0.8831 | 0.8428 |
+| 0.4161        | 4.6590 | 12500 | 0.5503          | 0.8650   | 0.8391    | 0.8925 | 0.8513   | 0.8910 | 0.8501 |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.3.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.19.0

config.json

@@ -0,0 +1,32 @@
+{
+  "_name_or_path": "AIRI-Institute/gena-lm-bert-base-t2t-multi",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "auto_map": {
+    "AutoModel": "AIRI-Institute/gena-lm-bert-base-t2t-multi--modeling_bert.BertForMaskedLM"
+  },
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "last_layer_norm": false,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 3,
+  "position_embedding_type": "absolute",
+  "pre_layer_norm": true,
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.42.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 32000
+}

model.safetensors

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special_tokens_map.json

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+{
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+    "content": "[CLS]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "mask_token": {
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+    "single_word": false
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+  "pad_token": {
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+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "sep_token": {
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+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "unk_token": {
+    "content": "[UNK]",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "special": true
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+      "normalized": false,
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+      "single_word": false,
+      "special": true
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+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "unk_token": "[UNK]"
+}

training_args.bin

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