End of training

README.md

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+---
+license: apache-2.0
+base_model: yhavinga/t5-small-24L-ccmatrix-multi
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- precision
+- recall
+model-index:
+- name: final_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. -->
+
+# final_classification
+
+This model is a fine-tuned version of [yhavinga/t5-small-24L-ccmatrix-multi](https://huggingface.co/yhavinga/t5-small-24L-ccmatrix-multi) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0945
+- F1: {'f1': 0.9405940594059407}
+- Precision: {'precision': 0.9134615384615384}
+- Recall: {'recall': 0.9693877551020408}
+
+## 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: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1                         | Precision                         | Recall                         |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------:|:---------------------------------:|:------------------------------:|
+| No log        | 1.0   | 110  | 0.2338          | {'f1': 0.6845637583892618} | {'precision': 1.0}                | {'recall': 0.5204081632653061} |
+| No log        | 2.0   | 220  | 0.0828          | {'f1': 0.9387755102040817} | {'precision': 0.9387755102040817} | {'recall': 0.9387755102040817} |
+| No log        | 3.0   | 330  | 0.0891          | {'f1': 0.9359605911330049} | {'precision': 0.9047619047619048} | {'recall': 0.9693877551020408} |
+| No log        | 4.0   | 440  | 0.0744          | {'f1': 0.95}               | {'precision': 0.9313725490196079} | {'recall': 0.9693877551020408} |
+| 0.1529        | 5.0   | 550  | 0.1012          | {'f1': 0.9405940594059407} | {'precision': 0.9134615384615384} | {'recall': 0.9693877551020408} |
+| 0.1529        | 6.0   | 660  | 0.0945          | {'f1': 0.9405940594059407} | {'precision': 0.9134615384615384} | {'recall': 0.9693877551020408} |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

model.safetensors

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