Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
custom_code
text-embeddings-inference
Instructions to use LiukG/gut_1024-finetuned-lora-bert-base-t2t-multi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LiukG/gut_1024-finetuned-lora-bert-base-t2t-multi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="LiukG/gut_1024-finetuned-lora-bert-base-t2t-multi", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("LiukG/gut_1024-finetuned-lora-bert-base-t2t-multi", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("LiukG/gut_1024-finetuned-lora-bert-base-t2t-multi", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files- README.md +71 -0
- config.json +32 -0
- model.safetensors +3 -0
- runs/Mar01_13-41-20_668f26dafc43/events.out.tfevents.1709300480.668f26dafc43.145.0 +3 -0
- special_tokens_map.json +37 -0
- tokenizer.json +0 -0
- tokenizer_config.json +60 -0
- training_args.bin +3 -0
README.md
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---
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base_model: AIRI-Institute/gena-lm-bert-base-t2t-multi
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tags:
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- generated_from_trainer
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metrics:
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- f1
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- accuracy
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model-index:
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- name: gut_1024-finetuned-lora-bert-base-t2t-multi
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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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# gut_1024-finetuned-lora-bert-base-t2t-multi
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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.
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It achieves the following results on the evaluation set:
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- Loss: 0.4764
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- F1: 0.8478
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- Mcc Score: 0.5903
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- Accuracy: 0.8049
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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: 0.0005
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- train_batch_size: 8
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- eval_batch_size: 64
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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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- training_steps: 1000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1 | Mcc Score | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:--------:|
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| 0.7012 | 0.02 | 100 | 0.6683 | 0.7478 | 0.0 | 0.5971 |
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| 0.7003 | 0.04 | 200 | 0.6391 | 0.7825 | 0.3306 | 0.6710 |
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| 0.6583 | 0.05 | 300 | 0.6211 | 0.7853 | 0.3430 | 0.6778 |
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| 0.6381 | 0.07 | 400 | 0.6512 | 0.7812 | 0.3247 | 0.6681 |
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| 0.6438 | 0.09 | 500 | 0.6524 | 0.3380 | 0.1874 | 0.5004 |
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| 0.6028 | 0.11 | 600 | 0.5646 | 0.8004 | 0.5013 | 0.7606 |
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| 0.5154 | 0.12 | 700 | 0.5437 | 0.8392 | 0.5576 | 0.7884 |
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| 0.5226 | 0.14 | 800 | 0.4823 | 0.8503 | 0.5901 | 0.8024 |
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| 0.5104 | 0.16 | 900 | 0.4856 | 0.8452 | 0.5851 | 0.8028 |
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| 0.5538 | 0.18 | 1000 | 0.4764 | 0.8478 | 0.5903 | 0.8049 |
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### Framework versions
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- Transformers 4.38.1
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- Pytorch 2.1.0+cu121
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- Datasets 2.17.1
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- Tokenizers 0.15.2
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config.json
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{
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"_name_or_path": "AIRI-Institute/gena-lm-bert-base-t2t-multi",
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"architectures": [
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"BertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"auto_map": {
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"AutoModel": "AIRI-Institute/gena-lm-bert-base-t2t-multi--modeling_bert.BertForMaskedLM"
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},
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"last_layer_norm": false,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 3,
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"position_embedding_type": "absolute",
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"pre_layer_norm": true,
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.38.1",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 32000
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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 sha256:9f957981cff03dde0cc13abca23df2ccd850604327c7e4e99cc93d523fa3e33e
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size 556061376
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runs/Mar01_13-41-20_668f26dafc43/events.out.tfevents.1709300480.668f26dafc43.145.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:247fc039105493001b21407f21588f8ed9f07a316a868d2efdf4bca83b2a3e0d
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size 11515
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special_tokens_map.json
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{
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"cls_token": {
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"mask_token": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"sep_token": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"unk_token": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer.json
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The diff for this file is too large to render.
See raw diff
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tokenizer_config.json
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{
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"added_tokens_decoder": {
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"0": {
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"content": "[UNK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "[CLS]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"2": {
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"content": "[SEP]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"3": {
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"content": "[PAD]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"4": {
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"content": "[MASK]",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"5": {
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"content": "-",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"clean_up_tokenization_spaces": true,
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"cls_token": "[CLS]",
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| 54 |
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"mask_token": "[MASK]",
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| 55 |
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"model_max_length": 1000000000000000019884624838656,
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| 56 |
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"pad_token": "[PAD]",
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| 57 |
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"sep_token": "[SEP]",
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"tokenizer_class": "PreTrainedTokenizerFast",
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"unk_token": "[UNK]"
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}
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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:f40514be1bfcfcdbf79222833532e226df5f787fc91ba8d265b285166690b400
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size 4920
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