trainer: training complete at 2024-02-06 19:14:46.426746.

README.md

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+---
+license: apache-2.0
+base_model: allenai/longformer-base-4096
+tags:
+- generated_from_trainer
+datasets:
+- fancy_dataset
+metrics:
+- accuracy
+model-index:
+- name: longformer-simple
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: fancy_dataset
+      type: fancy_dataset
+      config: simple
+      split: test
+      args: simple
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8226736894908453
+---
+
+<!-- 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. -->
+
+# longformer-simple
+
+This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the fancy_dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4587
+- Claim: {'precision': 0.5772692208794035, 'recall': 0.5279868297271872, 'f1-score': 0.5515292961552635, 'support': 4252.0}
+- Majorclaim: {'precision': 0.6656682890303257, 'recall': 0.8148487626031164, 'f1-score': 0.7327426334226252, 'support': 2182.0}
+- O: {'precision': 0.9301160937855679, 'recall': 0.8810781671159029, 'f1-score': 0.9049332816566081, 'support': 9275.0}
+- Premise: {'precision': 0.8568813181564913, 'recall': 0.8823770491803279, 'f1-score': 0.8694423131284578, 'support': 12200.0}
+- Accuracy: 0.8227
+- Macro avg: {'precision': 0.757483730462947, 'recall': 0.7765727021566337, 'f1-score': 0.7646618810907386, 'support': 27909.0}
+- Weighted avg: {'precision': 0.8236703495364839, 'recall': 0.8226736894908453, 'f1-score': 0.8221147085496641, 'support': 27909.0}
+
+## 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
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Claim                                                                                                                | Majorclaim                                                                                                         | O                                                                                                                  | Premise                                                                                                             | Accuracy | Macro avg                                                                                                           | Weighted avg                                                                                                        |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|:--------:|:-------------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------:|
+| No log        | 1.0   | 41   | 0.5844          | {'precision': 0.4909433962264151, 'recall': 0.30597365945437444, 'f1-score': 0.37699217618081715, 'support': 4252.0} | {'precision': 0.5969423210562891, 'recall': 0.3936755270394134, 'f1-score': 0.4744545705606187, 'support': 2182.0} | {'precision': 0.825323567773653, 'recall': 0.886900269541779, 'f1-score': 0.8550046772684753, 'support': 9275.0}   | {'precision': 0.8012704829278856, 'recall': 0.9098360655737705, 'f1-score': 0.8521091620926572, 'support': 12200.0} | 0.7699   | {'precision': 0.6786199419960607, 'recall': 0.6240963804023343, 'f1-score': 0.639640146525642, 'support': 27909.0}  | {'precision': 0.7460100844931877, 'recall': 0.7698591852090724, 'f1-score': 0.7511602266394221, 'support': 27909.0} |
+| No log        | 2.0   | 82   | 0.4763          | {'precision': 0.5736620565243535, 'recall': 0.4487300094073377, 'f1-score': 0.5035629453681709, 'support': 4252.0}   | {'precision': 0.7095454545454546, 'recall': 0.7153987167736022, 'f1-score': 0.7124600638977636, 'support': 2182.0} | {'precision': 0.8935006435006435, 'recall': 0.8982210242587602, 'f1-score': 0.8958546158395613, 'support': 9275.0} | {'precision': 0.8362814916915537, 'recall': 0.8951639344262295, 'f1-score': 0.8647214854111407, 'support': 12200.0} | 0.8141   | {'precision': 0.7532474115655013, 'recall': 0.7393784212164823, 'f1-score': 0.7441497776291592, 'support': 27909.0} | {'precision': 0.8053779036606528, 'recall': 0.8141101436812498, 'f1-score': 0.80814042735527, 'support': 27909.0}   |
+| No log        | 3.0   | 123  | 0.4587          | {'precision': 0.5772692208794035, 'recall': 0.5279868297271872, 'f1-score': 0.5515292961552635, 'support': 4252.0}   | {'precision': 0.6656682890303257, 'recall': 0.8148487626031164, 'f1-score': 0.7327426334226252, 'support': 2182.0} | {'precision': 0.9301160937855679, 'recall': 0.8810781671159029, 'f1-score': 0.9049332816566081, 'support': 9275.0} | {'precision': 0.8568813181564913, 'recall': 0.8823770491803279, 'f1-score': 0.8694423131284578, 'support': 12200.0} | 0.8227   | {'precision': 0.757483730462947, 'recall': 0.7765727021566337, 'f1-score': 0.7646618810907386, 'support': 27909.0}  | {'precision': 0.8236703495364839, 'recall': 0.8226736894908453, 'f1-score': 0.8221147085496641, 'support': 27909.0} |
+
+
+### Framework versions
+
+- Transformers 4.37.1
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

model.safetensors

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