transformers tensorboard safetensors pegasus text2text-generation generated_from_trainer base_model:google/pegasus-xsum autotrain_compatible endpoints_compatible region:us
---
base_model: google/pegasus-xsum
tags:
- generated_from_trainer
metrics:
- rouge
- precision
- recall
- f1
model-index:
- name: LLM_Teached_Pegasus_50k
  results: []
---

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# LLM_Teached_Pegasus_50k

This model is a fine-tuned version of [google/pegasus-xsum](https://huggingface.co/google/pegasus-xsum) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5934
- Rouge1: 0.4774
- Rouge2: 0.2259
- Rougel: 0.3926
- Rougelsum: 0.3926
- Gen Len: 26.5556
- Precision: 0.9117
- Recall: 0.9103
- F1: 0.9108

## 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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | F1     | Gen Len | Validation Loss | Precision | Recall | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:------:|:-------:|:---------------:|:---------:|:------:|:------:|:------:|:------:|:---------:|
| No log        | 1.0   | 390   | 0.9034 | 26.2967 | 1.8258          | 0.9049    | 0.9023 | 0.4338 | 0.1906 | 0.3496 | 0.3498    |
| 2.1621        | 2.0   | 781   | 0.9054 | 26.2727 | 1.7537          | 0.9068    | 0.9044 | 0.4449 | 0.2005 | 0.3633 | 0.3633    |
| 1.8794        | 3.0   | 1172  | 0.9066 | 26.4345 | 1.7268          | 0.9078    | 0.9058 | 0.4518 | 0.2061 | 0.3696 | 0.3695    |
| 1.8271        | 4.0   | 1560  | 0.9069 | 26.3971 | 1.7157          | 0.9082    | 0.906  | 0.4539 | 0.2075 | 0.3716 | 0.3714    |
| 1.8271        | 5.0   | 1951  | 0.9074 | 26.3015 | 1.7033          | 0.9087    | 0.9065 | 0.4561 | 0.2098 | 0.3735 | 0.3734    |
| 1.8067        | 6.0   | 2340  | 0.9077 | 26.4389 | 1.6897          | 0.9089    | 0.9069 | 0.4592 | 0.2114 | 0.3762 | 0.3759    |
| 1.7833        | 7.0   | 2731  | 0.9079 | 26.3745 | 1.6819          | 0.9092    | 0.9071 | 0.4598 | 0.2115 | 0.3764 | 0.376     |
| 1.7683        | 8.0   | 3120  | 0.9083 | 26.6204 | 1.6763          | 0.9094    | 0.9076 | 0.4621 | 0.2133 | 0.3791 | 0.3789    |
| 1.7559        | 9.0   | 3511  | 0.9086 | 26.424  | 1.6662          | 0.9098    | 0.9078 | 0.4632 | 0.215  | 0.38   | 0.3799    |
| 1.7559        | 10.0  | 3902  | 0.9089 | 26.5425 | 1.6594          | 0.9099    | 0.9082 | 0.4651 | 0.2168 | 0.3812 | 0.3812    |
| 1.7357        | 11.0  | 4293  | 0.9091 | 26.6051 | 1.6555          | 0.91      | 0.9086 | 0.4663 | 0.2178 | 0.3824 | 0.3823    |
| 1.7297        | 12.0  | 4680  | 0.9092 | 26.4393 | 1.6508          | 0.9103    | 0.9084 | 0.4668 | 0.2175 | 0.3823 | 0.3822    |
| 1.7165        | 13.0  | 5071  | 0.9094 | 26.6385 | 1.6451          | 0.9103    | 0.9089 | 0.4687 | 0.2191 | 0.3834 | 0.3834    |
| 1.7165        | 14.0  | 5462  | 0.9095 | 26.4156 | 1.6405          | 0.9106    | 0.9087 | 0.4691 | 0.2193 | 0.3845 | 0.3844    |
| 1.7068        | 15.0  | 5853  | 0.9097 | 26.4571 | 1.6383          | 0.9108    | 0.9089 | 0.4699 | 0.2204 | 0.3853 | 0.3853    |
| 1.7004        | 16.0  | 6240  | 0.9097 | 26.4247 | 1.6346          | 0.9108    | 0.9089 | 0.4703 | 0.2204 | 0.385  | 0.385     |
| 1.6923        | 17.0  | 6631  | 0.9099 | 26.4436 | 1.6305          | 0.911     | 0.9091 | 0.4706 | 0.221  | 0.3855 | 0.3856    |
| 1.6839        | 18.0  | 7022  | 0.9098 | 26.612  | 1.6285          | 0.9106    | 0.9094 | 0.4712 | 0.2215 | 0.3862 | 0.3864    |
| 1.6839        | 19.0  | 7413  | 0.9099 | 26.5291 | 1.6263          | 0.9108    | 0.9093 | 0.4709 | 0.2217 | 0.3862 | 0.3864    |
| 1.6743        | 20.0  | 7800  | 0.91   | 26.4251 | 1.6205          | 0.9111    | 0.9092 | 0.4727 | 0.2223 | 0.3876 | 0.3876    |
| 1.6692        | 21.0  | 8191  | 0.9102 | 26.7484 | 1.6153          | 0.911     | 0.9098 | 0.4737 | 0.2229 | 0.388  | 0.388     |
| 1.6568        | 22.0  | 8582  | 0.9103 | 26.532  | 1.6104          | 0.9113    | 0.9096 | 0.4733 | 0.2221 | 0.3885 | 0.3886    |
| 1.6568        | 23.0  | 8973  | 0.9104 | 26.82   | 1.6056          | 0.911     | 0.9101 | 0.4756 | 0.2236 | 0.3891 | 0.3891    |
| 1.6418        | 24.0  | 9360  | 1.6021 | 0.476   | 0.2246          | 0.3903    | 0.3903 | 26.5513| 0.9115 | 0.91   | 0.9106    |
| 1.6319        | 25.0  | 9751  | 1.5995 | 0.4751  | 0.2245          | 0.3905    | 0.3905 | 26.4375| 0.9116 | 0.9098 | 0.9105    |
| 1.624         | 26.0  | 10142 | 1.5974 | 0.4756  | 0.2247          | 0.3903    | 0.3904 | 26.6018| 0.9116 | 0.9101 | 0.9107    |
| 1.6184        | 27.0  | 10533 | 1.5953 | 0.4747  | 0.2231          | 0.3899    | 0.3899 | 26.4833| 0.9116 | 0.9099 | 0.9106    |
| 1.6184        | 28.0  | 10923 | 1.5943 | 0.4758  | 0.2243          | 0.3907    | 0.3908 | 26.5604| 0.9116 | 0.9102 | 0.9107    |
| 1.6126        | 29.0  | 11314 | 1.5936 | 0.4776  | 0.226           | 0.3926    | 0.3926 | 26.5775| 0.9117 | 0.9103 | 0.9108    |
| 1.6148        | 29.99 | 11700 | 1.5934 | 0.4774  | 0.2259          | 0.3926    | 0.3926 | 26.5556| 0.9117 | 0.9103 | 0.9108    |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0
