Abdo36/DistilBertLoRa

README.md

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 ---
 license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: distilbert-base-uncased
+metrics:
+- accuracy
+model-index:
+- name: DistilBertLoRa
+  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. -->
+
+# DistilBertLoRa
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0234
+- Accuracy: {'accuracy': 0.884}
+
+## 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            |
+|:-------------:|:-----:|:----:|:---------------:|:-------------------:|
+| No log        | 1.0   | 250  | 0.4076          | {'accuracy': 0.876} |
+| 0.429         | 2.0   | 500  | 0.3507          | {'accuracy': 0.863} |
+| 0.429         | 3.0   | 750  | 0.5018          | {'accuracy': 0.881} |
+| 0.2304        | 4.0   | 1000 | 0.7036          | {'accuracy': 0.864} |
+| 0.2304        | 5.0   | 1250 | 0.8113          | {'accuracy': 0.862} |
+| 0.1136        | 6.0   | 1500 | 0.8428          | {'accuracy': 0.882} |
+| 0.1136        | 7.0   | 1750 | 0.9134          | {'accuracy': 0.89}  |
+| 0.0153        | 8.0   | 2000 | 0.9723          | {'accuracy': 0.884} |
+| 0.0153        | 9.0   | 2250 | 1.0225          | {'accuracy': 0.884} |
+| 0.0089        | 10.0  | 2500 | 1.0234          | {'accuracy': 0.884} |
+
+
+### Framework versions
+
+- PEFT 0.10.0
+- Transformers 4.40.0
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

adapter_model.safetensors

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runs/Apr26_13-28-13_bf6f4f9ea73a/events.out.tfevents.1714138097.bf6f4f9ea73a.790.0

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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,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "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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