paduraru2009/distilbert-base-uncased-sentimentanalysis-demo

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: distilbert-base-uncased-lora-text-classification
+  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. -->
+
+# distilbert-base-uncased-lora-text-classification
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5479
+- Accuracy: {'accuracy': 0.7540666666666667}
+
+## 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: 0.001
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy                         |
+|:-------------:|:-----:|:-----:|:---------------:|:--------------------------------:|
+| 0.6425        | 1.0   | 7500  | 0.5937          | {'accuracy': 0.8124}             |
+| 0.6312        | 2.0   | 15000 | 0.6853          | {'accuracy': 0.6939}             |
+| 0.6127        | 3.0   | 22500 | 0.5976          | {'accuracy': 0.7106333333333333} |
+| 0.6043        | 4.0   | 30000 | 0.5694          | {'accuracy': 0.7357}             |
+| 0.5742        | 5.0   | 37500 | 0.6108          | {'accuracy': 0.7456333333333334} |
+| 0.5527        | 6.0   | 45000 | 0.5915          | {'accuracy': 0.7628333333333334} |
+| 0.615         | 7.0   | 52500 | 0.5992          | {'accuracy': 0.7109333333333333} |
+| 0.5847        | 8.0   | 60000 | 0.5428          | {'accuracy': 0.7357333333333334} |
+| 0.5767        | 9.0   | 67500 | 0.5650          | {'accuracy': 0.7488333333333334} |
+| 0.5463        | 10.0  | 75000 | 0.5479          | {'accuracy': 0.7540666666666667} |
+
+
+### Framework versions
+
+- Transformers 4.32.1
+- Pytorch 2.1.0+cu121
+- Datasets 2.14.6
+- Tokenizers 0.13.2

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "distilbert-base-uncased",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 32,
+  "lora_dropout": 0.01,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 4,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v_lin",
+    "q_lin"
+  ],
+  "task_type": "SEQ_CLS"
+}

adapter_model.bin

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special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "add_prefix_space": true,
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "DistilBertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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