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--- |
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base_model: UrukHan/t5-russian-summarization |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: last_run_UrukHan_t5-russian-summarization |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/diffraction-zebra/RoseltorgItemsTunning/runs/3b4e0ldl) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/diffraction-zebra/RoseltorgItemsTunning/runs/pvl2qfvv) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/diffraction-zebra/RoseltorgItemsTunning/runs/o04syxyd) |
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# last_run_UrukHan_t5-russian-summarization |
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This model is a fine-tuned version of [UrukHan/t5-russian-summarization](https://huggingface.co/UrukHan/t5-russian-summarization) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6429 |
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- F1: 0.4241 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.00012 |
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- train_batch_size: 4 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 7.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:------:| |
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| 0.8758 | 0.6667 | 200 | 0.9457 | 0.3173 | |
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| 0.7212 | 1.3333 | 400 | 0.8009 | 0.3486 | |
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| 0.5636 | 2.0 | 600 | 0.7738 | 0.3699 | |
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| 0.4931 | 2.6667 | 800 | 0.7189 | 0.3951 | |
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| 0.4748 | 3.3333 | 1000 | 0.6766 | 0.4020 | |
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| 0.4125 | 4.0 | 1200 | 0.6658 | 0.4143 | |
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| 0.3326 | 4.6667 | 1400 | 0.6481 | 0.4243 | |
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| 0.2676 | 5.3333 | 1600 | 0.6494 | 0.4063 | |
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| 0.3643 | 6.0 | 1800 | 0.6383 | 0.4175 | |
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| 0.2064 | 6.6667 | 2000 | 0.6429 | 0.4241 | |
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### Framework versions |
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- Transformers 4.43.1 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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