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qqq-finetuned-on-calls

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+ ---
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+ license: mit
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: qqq-finetuned-on-calls
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+ results: []
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+ ---
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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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+
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+ # qqq-finetuned-on-calls
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+
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+ This model is a fine-tuned version of [bragovo/qqq](https://huggingface.co/bragovo/qqq) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0021
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+ - Rouge-1: 1.0
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+ - Rouge-2: 1.0
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+ - Rouge-l: 1.0
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+ - Gen Len: 11.0
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+ - Avg Rouge F: 1.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 3
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+ - eval_batch_size: 1
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+ - seed: 42
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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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+ - lr_scheduler_warmup_steps: 50
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+ - num_epochs: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Avg Rouge F |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:-----------:|
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+ | 2.1855 | 3.12 | 25 | 1.4282 | 0.0 | 0.0 | 0.0 | 15.0 | 0.0 |
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+ | 1.5665 | 6.25 | 50 | 0.6420 | 0.1818 | 0.0 | 0.1818 | 12.0 | 0.1212 |
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+ | 1.1046 | 9.38 | 75 | 0.2184 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.8218 | 12.5 | 100 | 0.1098 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.606 | 15.62 | 125 | 0.0749 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.5488 | 18.75 | 150 | 0.0577 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.4161 | 21.88 | 175 | 0.0684 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.3196 | 25.0 | 200 | 0.0570 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.2929 | 28.12 | 225 | 0.0416 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.2519 | 31.25 | 250 | 0.0247 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.178 | 34.38 | 275 | 0.0118 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.1603 | 37.5 | 300 | 0.0064 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.1684 | 40.62 | 325 | 0.0051 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.1326 | 43.75 | 350 | 0.0051 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.1349 | 46.88 | 375 | 0.0064 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.1105 | 50.0 | 400 | 0.0061 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.1026 | 53.12 | 425 | 0.0049 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.0936 | 56.25 | 450 | 0.0030 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.0704 | 59.38 | 475 | 0.0025 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.0699 | 62.5 | 500 | 0.0021 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.0863 | 65.62 | 525 | 0.0020 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.0595 | 68.75 | 550 | 0.0024 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.0594 | 71.88 | 575 | 0.0028 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.0683 | 75.0 | 600 | 0.0026 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+ | 0.074 | 78.12 | 625 | 0.0025 | 1.0 | 1.0 | 1.0 | 11.0 | 1.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.29.0
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+ - Pytorch 2.0.0+cu118
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.3