tjasadprompt_fine_tuned_boolq__XLMroberta

.gitattributes

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+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+license: mit
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: xlm-roberta-base
+metrics:
+- accuracy
+- f1
+model-index:
+- name: prompt_fine_tuned_boolq__XLMroberta
+  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. -->
+
+# prompt_fine_tuned_boolq__XLMroberta
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5694
+- Accuracy: 0.7778
+- F1: 0.6806
+
+## 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: 2e-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
+- training_steps: 400
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
+| 0.6671        | 4.1667  | 50   | 0.5942          | 0.7778   | 0.6806 |
+| 0.6529        | 8.3333  | 100  | 0.5786          | 0.7778   | 0.6806 |
+| 0.6499        | 12.5    | 150  | 0.5779          | 0.7778   | 0.6806 |
+| 0.6527        | 16.6667 | 200  | 0.5782          | 0.7778   | 0.6806 |
+| 0.6471        | 20.8333 | 250  | 0.5716          | 0.7778   | 0.6806 |
+| 0.6533        | 25.0    | 300  | 0.5710          | 0.7778   | 0.6806 |
+| 0.6599        | 29.1667 | 350  | 0.5691          | 0.7778   | 0.6806 |
+| 0.6552        | 33.3333 | 400  | 0.5694          | 0.7778   | 0.6806 |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.40.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

adapter_config.json

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+{
+  "auto_mapping": null,
+  "base_model_name_or_path": "xlm-roberta-base",
+  "inference_mode": true,
+  "num_attention_heads": 12,
+  "num_layers": 6,
+  "num_transformer_submodules": 1,
+  "num_virtual_tokens": 12,
+  "peft_type": "PROMPT_TUNING",
+  "prompt_tuning_init": "RANDOM",
+  "prompt_tuning_init_text": null,
+  "revision": null,
+  "task_type": "SEQ_CLS",
+  "token_dim": 768,
+  "tokenizer_kwargs": null,
+  "tokenizer_name_or_path": "xlm-roberta-base"
+}

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runs/May23_08-21-27_eb4cf4039fb0/events.out.tfevents.1716452488.eb4cf4039fb0.1492.0

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tokenizer_config.json

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+}

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