transformers pytorch tensorboard bart text2text-generation summarization generated_from_trainer autotrain_compatible endpoints_compatible region:us
---
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: bart-large-cnn-samsum-rescom-finetuned-resume-summarizer-10-epoch-tweak-lr-8-100-1
  results: []
---

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# bart-large-cnn-samsum-rescom-finetuned-resume-summarizer-10-epoch-tweak-lr-8-100-1

This model is a fine-tuned version of [Ameer05/model-token-repo](https://huggingface.co/Ameer05/model-token-repo) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6315
- Rouge1: 61.441
- Rouge2: 52.9403
- Rougel: 58.3426
- Rougelsum: 60.8249

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| No log        | 0.91  | 5    | 2.0139          | 53.4301 | 46.6698 | 50.644  | 53.3985   |
| No log        | 1.91  | 10   | 1.6309          | 61.4629 | 53.8884 | 59.0867 | 60.8823   |
| No log        | 2.91  | 15   | 1.5379          | 61.2938 | 53.7208 | 59.0644 | 60.7381   |
| No log        | 3.91  | 20   | 1.4470          | 63.2667 | 55.9273 | 60.5112 | 62.7538   |
| 1.5454        | 4.91  | 25   | 1.4353          | 62.7166 | 54.8328 | 60.0101 | 62.1378   |
| 1.5454        | 5.91  | 30   | 1.4411          | 59.7469 | 51.9068 | 57.036  | 58.9474   |
| 1.5454        | 6.91  | 35   | 1.5195          | 64.152  | 57.1447 | 61.362  | 63.5951   |
| 1.5454        | 7.91  | 40   | 1.6174          | 60.1464 | 51.5654 | 57.1676 | 59.4405   |
| 0.5429        | 8.91  | 45   | 1.7451          | 61.9696 | 53.6421 | 58.5884 | 61.3286   |
| 0.5429        | 9.91  | 50   | 1.9081          | 60.3296 | 52.3052 | 57.6518 | 59.7854   |
| 0.5429        | 10.91 | 55   | 1.9721          | 61.5597 | 51.9027 | 57.1184 | 60.6717   |
| 0.5429        | 11.91 | 60   | 2.0471          | 61.2222 | 53.9475 | 58.725  | 60.6668   |
| 0.5429        | 12.91 | 65   | 2.1422          | 60.1915 | 52.0627 | 56.9955 | 59.438    |
| 0.1506        | 13.91 | 70   | 2.1542          | 61.6915 | 53.045  | 58.1727 | 60.8765   |
| 0.1506        | 14.91 | 75   | 2.1885          | 59.8069 | 51.6543 | 56.8112 | 59.2055   |
| 0.1506        | 15.91 | 80   | 2.3146          | 61.695  | 53.2666 | 57.9003 | 61.1108   |
| 0.1506        | 16.91 | 85   | 2.3147          | 60.4482 | 52.1694 | 57.0649 | 59.7882   |
| 0.0452        | 17.91 | 90   | 2.1731          | 60.0259 | 51.5046 | 56.7399 | 59.2955   |
| 0.0452        | 18.91 | 95   | 2.2690          | 60.0534 | 52.4819 | 57.1631 | 59.5056   |
| 0.0452        | 19.91 | 100  | 2.2990          | 58.0737 | 48.8098 | 54.5684 | 57.3187   |
| 0.0452        | 20.91 | 105  | 2.2704          | 61.8982 | 53.9077 | 58.6909 | 61.4252   |
| 0.0267        | 21.91 | 110  | 2.3012          | 62.0174 | 53.5427 | 58.5278 | 61.1921   |
| 0.0267        | 22.91 | 115  | 2.3569          | 61.6327 | 53.7387 | 58.8908 | 61.1623   |
| 0.0267        | 23.91 | 120  | 2.3579          | 60.228  | 52.3747 | 58.1448 | 59.7322   |
| 0.0267        | 24.91 | 125  | 2.3389          | 60.4902 | 51.7935 | 57.0689 | 59.7132   |
| 0.0267        | 25.91 | 130  | 2.3168          | 58.8469 | 50.3181 | 55.7386 | 58.3598   |
| 0.0211        | 26.91 | 135  | 2.4147          | 59.4225 | 50.8405 | 56.503  | 58.7221   |
| 0.0211        | 27.91 | 140  | 2.3631          | 59.7489 | 51.2137 | 57.3204 | 59.3348   |
| 0.0211        | 28.91 | 145  | 2.3850          | 60.1718 | 51.4176 | 57.2152 | 59.5157   |
| 0.0211        | 29.91 | 150  | 2.4610          | 60.1433 | 51.433  | 56.6256 | 59.3265   |
| 0.0175        | 30.91 | 155  | 2.4400          | 58.8345 | 49.7031 | 55.3079 | 57.9236   |
| 0.0175        | 31.91 | 160  | 2.4506          | 59.209  | 50.1626 | 55.6451 | 58.5791   |
| 0.0175        | 32.91 | 165  | 2.4316          | 59.7713 | 50.8999 | 56.4235 | 58.9845   |
| 0.0175        | 33.91 | 170  | 2.2781          | 60.1822 | 51.9435 | 57.4586 | 59.6766   |
| 0.0175        | 34.91 | 175  | 2.3849          | 58.2328 | 49.2106 | 55.1516 | 57.5072   |
| 0.0141        | 35.91 | 180  | 2.4872          | 58.4916 | 50.3345 | 55.5991 | 58.1131   |
| 0.0141        | 36.91 | 185  | 2.4883          | 59.0957 | 49.76   | 55.3567 | 58.076    |
| 0.0141        | 37.91 | 190  | 2.4327          | 58.091  | 48.8628 | 54.8678 | 57.5406   |
| 0.0141        | 38.91 | 195  | 2.4998          | 57.7428 | 48.7366 | 54.2166 | 56.7643   |
| 0.0089        | 39.91 | 200  | 2.4107          | 60.1662 | 51.9832 | 57.1372 | 59.6989   |
| 0.0089        | 40.91 | 205  | 2.4700          | 58.2159 | 49.3934 | 54.9265 | 57.4126   |
| 0.0089        | 41.91 | 210  | 2.4833          | 58.7434 | 49.6619 | 55.5239 | 57.9562   |
| 0.0089        | 42.91 | 215  | 2.4703          | 60.2984 | 51.3168 | 56.9082 | 59.3958   |
| 0.0062        | 43.91 | 220  | 2.5306          | 60.5455 | 52.1189 | 57.3213 | 60.0232   |
| 0.0062        | 44.91 | 225  | 2.5181          | 60.2149 | 51.2187 | 56.1935 | 59.3471   |
| 0.0062        | 45.91 | 230  | 2.4871          | 59.8013 | 51.6114 | 56.0911 | 59.0902   |
| 0.0062        | 46.91 | 235  | 2.4811          | 58.0271 | 48.9441 | 54.3108 | 57.3647   |
| 0.0062        | 47.91 | 240  | 2.5290          | 62.5087 | 54.6149 | 59.638  | 62.0455   |
| 0.0072        | 48.91 | 245  | 2.5194          | 58.7193 | 49.9679 | 55.6517 | 58.1569   |
| 0.0072        | 49.91 | 250  | 2.5708          | 58.4626 | 49.5257 | 54.5032 | 58.1413   |
| 0.0072        | 50.91 | 255  | 2.6449          | 58.446  | 49.4625 | 55.1092 | 58.03     |
| 0.0072        | 51.91 | 260  | 2.5592          | 58.859  | 49.4398 | 55.1503 | 57.9663   |
| 0.0056        | 52.91 | 265  | 2.5086          | 59.7322 | 51.3051 | 56.5401 | 59.2726   |
| 0.0056        | 53.91 | 270  | 2.4846          | 57.8603 | 48.2408 | 54.3847 | 57.115    |
| 0.0056        | 54.91 | 275  | 2.5509          | 58.9506 | 50.045  | 55.6658 | 58.3618   |
| 0.0056        | 55.91 | 280  | 2.5032          | 60.2524 | 51.8167 | 56.98   | 59.7506   |
| 0.0056        | 56.91 | 285  | 2.5012          | 60.0596 | 51.4924 | 56.7181 | 59.5037   |
| 0.0054        | 57.91 | 290  | 2.5176          | 61.0622 | 52.6235 | 57.9317 | 60.5036   |
| 0.0054        | 58.91 | 295  | 2.5024          | 62.9246 | 54.8544 | 59.9824 | 62.5584   |
| 0.0054        | 59.91 | 300  | 2.5687          | 62.2602 | 53.9673 | 58.9862 | 61.5837   |
| 0.0054        | 60.91 | 305  | 2.5890          | 62.5706 | 54.227  | 59.2032 | 62.125    |
| 0.0036        | 61.91 | 310  | 2.5454          | 62.1565 | 53.2585 | 58.7169 | 61.3943   |
| 0.0036        | 62.91 | 315  | 2.5629          | 62.8292 | 54.6781 | 59.9889 | 62.254    |
| 0.0036        | 63.91 | 320  | 2.5581          | 58.8394 | 50.4421 | 56.0742 | 58.1945   |
| 0.0036        | 64.91 | 325  | 2.5532          | 59.5814 | 51.1335 | 56.5841 | 59.196    |
| 0.0031        | 65.91 | 330  | 2.5826          | 59.0485 | 50.3992 | 55.5283 | 58.3757   |
| 0.0031        | 66.91 | 335  | 2.5815          | 61.4832 | 52.7977 | 57.7351 | 60.9888   |
| 0.0031        | 67.91 | 340  | 2.5865          | 61.7836 | 53.6797 | 58.6743 | 61.3765   |
| 0.0031        | 68.91 | 345  | 2.6007          | 61.2253 | 52.8781 | 57.7006 | 60.717    |
| 0.0031        | 69.91 | 350  | 2.6210          | 60.717  | 52.4933 | 57.5089 | 60.4196   |
| 0.0035        | 70.91 | 355  | 2.6169          | 61.3491 | 53.3932 | 58.2288 | 60.8793   |
| 0.0035        | 71.91 | 360  | 2.6025          | 62.0101 | 54.0289 | 59.0822 | 61.7202   |
| 0.0035        | 72.91 | 365  | 2.5705          | 61.2227 | 52.9937 | 58.2493 | 60.6631   |
| 0.0035        | 73.91 | 370  | 2.5623          | 59.1718 | 50.7827 | 56.1851 | 58.7118   |
| 0.002         | 74.91 | 375  | 2.5536          | 58.4201 | 49.6923 | 55.0398 | 57.7707   |
| 0.002         | 75.91 | 380  | 2.5478          | 60.2307 | 51.7503 | 57.3173 | 59.692    |
| 0.002         | 76.91 | 385  | 2.6039          | 58.7637 | 49.741  | 55.5341 | 58.0784   |
| 0.002         | 77.91 | 390  | 2.6371          | 59.3929 | 50.6444 | 55.9887 | 58.813    |
| 0.002         | 78.91 | 395  | 2.6238          | 59.0572 | 50.605  | 55.6631 | 58.4366   |
| 0.0019        | 79.91 | 400  | 2.5783          | 57.9852 | 49.2588 | 54.822  | 57.4643   |
| 0.0019        | 80.91 | 405  | 2.5982          | 58.0218 | 49.1651 | 54.9876 | 57.4066   |
| 0.0019        | 81.91 | 410  | 2.6141          | 60.3133 | 51.5723 | 56.9476 | 59.715    |
| 0.0019        | 82.91 | 415  | 2.5904          | 60.8199 | 51.8956 | 58.406  | 60.323    |
| 0.0017        | 83.91 | 420  | 2.5718          | 60.3449 | 51.1433 | 57.6984 | 59.7513   |
| 0.0017        | 84.91 | 425  | 2.5737          | 60.151  | 51.1986 | 57.3376 | 59.378    |
| 0.0017        | 85.91 | 430  | 2.5807          | 60.9273 | 52.2469 | 58.2038 | 60.1642   |
| 0.0017        | 86.91 | 435  | 2.5900          | 60.1846 | 51.6144 | 57.5407 | 59.5109   |
| 0.0011        | 87.91 | 440  | 2.6066          | 62.0776 | 53.6022 | 59.157  | 61.6201   |
| 0.0011        | 88.91 | 445  | 2.6231          | 61.8822 | 53.5232 | 58.965  | 61.401    |
| 0.0011        | 89.91 | 450  | 2.6273          | 60.3358 | 51.9941 | 57.3823 | 59.7729   |
| 0.0011        | 90.91 | 455  | 2.6194          | 60.0196 | 51.6134 | 57.1357 | 59.4594   |
| 0.0011        | 91.91 | 460  | 2.6118          | 60.6898 | 52.1328 | 57.3076 | 60.0351   |
| 0.0015        | 92.91 | 465  | 2.6032          | 61.2119 | 52.5034 | 57.8098 | 60.6634   |
| 0.0015        | 93.91 | 470  | 2.6040          | 61.4812 | 52.8197 | 57.9668 | 60.8767   |
| 0.0015        | 94.91 | 475  | 2.6158          | 61.4046 | 52.8905 | 57.8958 | 60.804    |
| 0.0015        | 95.91 | 480  | 2.6280          | 62.1764 | 53.8521 | 58.8608 | 61.6138   |
| 0.0012        | 96.91 | 485  | 2.6304          | 62.2028 | 53.8967 | 58.8976 | 61.6409   |
| 0.0012        | 97.91 | 490  | 2.6328          | 61.7371 | 53.3908 | 58.4107 | 61.1382   |
| 0.0012        | 98.91 | 495  | 2.6331          | 61.441  | 52.9403 | 58.3426 | 60.8249   |
| 0.0012        | 99.91 | 500  | 2.6315          | 61.441  | 52.9403 | 58.3426 | 60.8249   |


### Framework versions

- Transformers 4.15.0
- Pytorch 1.9.1
- Datasets 1.18.4
- Tokenizers 0.10.3
