End of training

README.md

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+---
+base_model: AIRI-Institute/gena-lm-bert-base-t2t-multi
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: mus_promoter-finetuned-lora-bert-base-t2t-multi
+  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. -->
+
+# mus_promoter-finetuned-lora-bert-base-t2t-multi
+
+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: 0.0021
+- F1: 1.0
+- Mcc Score: 1.0
+- Accuracy: 1.0
+
+## 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: 0.0005
+- train_batch_size: 8
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- training_steps: 1000
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Mcc Score | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:--------:|
+| 0.169         | 0.43  | 100  | 0.2552          | 0.9429 | 0.8814    | 0.9375   |
+| 0.1379        | 0.85  | 200  | 0.2600          | 0.9600 | 0.9039    | 0.9531   |
+| 0.0749        | 1.28  | 300  | 0.1726          | 0.9737 | 0.9373    | 0.9688   |
+| 0.0708        | 1.71  | 400  | 0.0171          | 0.9863 | 0.9686    | 0.9844   |
+| 0.0579        | 2.14  | 500  | 0.1011          | 0.9863 | 0.9686    | 0.9844   |
+| 0.0512        | 2.56  | 600  | 0.0993          | 0.9722 | 0.9385    | 0.9688   |
+| 0.0238        | 2.99  | 700  | 0.0065          | 1.0    | 1.0       | 1.0      |
+| 0.0108        | 3.42  | 800  | 0.0605          | 0.9863 | 0.9686    | 0.9844   |
+| 0.024         | 3.85  | 900  | 0.0029          | 1.0    | 1.0       | 1.0      |
+| 0.0178        | 4.27  | 1000 | 0.0021          | 1.0    | 1.0       | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.2

config.json

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+{
+  "_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": "4.37.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 32000
+}

model.safetensors

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runs/Feb28_14-30-45_3647a9057f0c/events.out.tfevents.1709130646.3647a9057f0c.154.0

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special_tokens_map.json

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tokenizer_config.json

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+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "unk_token": "[UNK]"
+}

training_args.bin

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