End of training

README.md

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+---
+license: mit
+base_model: ingeniumacademy/bart-cnn-samsum-finetuned
+tags:
+- generated_from_trainer
+datasets:
+- samsum
+model-index:
+- name: bart-cnn-samsum-peft
+  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. -->
+
+# bart-cnn-samsum-peft
+
+This model is a fine-tuned version of [ingeniumacademy/bart-cnn-samsum-finetuned](https://huggingface.co/ingeniumacademy/bart-cnn-samsum-finetuned) on the samsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2544
+
+## 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: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.0769        | 1.0   | 74   | 0.2544          |
+
+
+### Framework versions
+
+- Transformers 4.33.1
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

adapter_config.json

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+{
+  "auto_mapping": null,
+  "base_model_name_or_path": "ingeniumacademy/bart-cnn-samsum-finetuned",
+  "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": 0.05,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 32,
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "SEQ_2_SEQ_LM"
+}

adapter_model.bin

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training_args.bin

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