readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - ccdv/arxiv-summarization
  metrics:
  - rouge
  model-index:
  - name: arxiv-summarization-t5-base-2022-09-21
    results:
    - task:
        name: Summarization
        type: summarization
      dataset:
        name: ccdv/arxiv-summarization
        type: ccdv/arxiv-summarization
        config: section
        split: train
        args: section
      metrics:
      - name: Rouge1
        type: rouge
        value: 40.6781
  ---
  
  <!-- 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. -->
  
  # arxiv-summarization-t5-base-2022-09-21
  
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the ccdv/arxiv-summarization dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8650
  - Rouge1: 40.6781
  - Rouge2: 14.7167
  - Rougel: 26.6375
  - Rougelsum: 35.5959
  - Gen Len: 117.1969
  
  ## 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: 1
  - eval_batch_size: 1
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3.0
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:------:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 2.3291        | 0.05  | 10000  | 2.1906          | 18.6571 | 7.1341 | 14.8347 | 16.9545   | 19.0    |
  | 2.2454        | 0.1   | 20000  | 2.1549          | 18.5037 | 7.1908 | 14.7141 | 16.8233   | 18.9997 |
  | 2.2107        | 0.15  | 30000  | 2.1013          | 18.7638 | 7.326  | 14.9437 | 17.072    | 19.0    |
  | 2.1486        | 0.2   | 40000  | 2.0845          | 18.6879 | 7.2441 | 14.8835 | 16.983    | 19.0    |
  | 2.158         | 0.25  | 50000  | 2.0699          | 18.8314 | 7.3712 | 15.0166 | 17.1215   | 19.0    |
  | 2.1476        | 0.3   | 60000  | 2.0424          | 18.9783 | 7.4138 | 15.1121 | 17.2778   | 18.9981 |
  | 2.1164        | 0.34  | 70000  | 2.0349          | 18.9257 | 7.4649 | 15.0335 | 17.1819   | 19.0    |
  | 2.079         | 0.39  | 80000  | 2.0208          | 18.643  | 7.4096 | 14.8927 | 16.9786   | 18.9994 |
  | 2.101         | 0.44  | 90000  | 2.0113          | 19.3881 | 7.7012 | 15.3981 | 17.6516   | 19.0    |
  | 2.0576        | 0.49  | 100000 | 2.0022          | 18.9985 | 7.542  | 15.1157 | 17.2972   | 18.9992 |
  | 2.0983        | 0.54  | 110000 | 1.9941          | 18.7691 | 7.4625 | 15.0256 | 17.1146   | 19.0    |
  | 2.053         | 0.59  | 120000 | 1.9855          | 19.002  | 7.5602 | 15.1497 | 17.2963   | 19.0    |
  | 2.0434        | 0.64  | 130000 | 1.9786          | 19.2385 | 7.6533 | 15.3094 | 17.5439   | 18.9994 |
  | 2.0354        | 0.69  | 140000 | 1.9746          | 19.184  | 7.7307 | 15.2897 | 17.491    | 18.9992 |
  | 2.0347        | 0.74  | 150000 | 1.9639          | 19.2408 | 7.693  | 15.3357 | 17.5297   | 19.0    |
  | 2.0236        | 0.79  | 160000 | 1.9590          | 19.0781 | 7.6256 | 15.1932 | 17.3486   | 18.9998 |
  | 2.0187        | 0.84  | 170000 | 1.9532          | 19.0343 | 7.6792 | 15.1884 | 17.3519   | 19.0    |
  | 1.9939        | 0.89  | 180000 | 1.9485          | 18.8247 | 7.5005 | 15.0246 | 17.1485   | 18.9998 |
  | 1.9961        | 0.94  | 190000 | 1.9504          | 19.0695 | 7.6559 | 15.2139 | 17.3814   | 19.0    |
  | 2.0197        | 0.99  | 200000 | 1.9399          | 19.2821 | 7.6685 | 15.3029 | 17.5374   | 18.9988 |
  | 1.9457        | 1.03  | 210000 | 1.9350          | 19.053  | 7.6502 | 15.2123 | 17.3793   | 19.0    |
  | 1.9552        | 1.08  | 220000 | 1.9317          | 19.1878 | 7.7235 | 15.3272 | 17.5252   | 18.9998 |
  | 1.9772        | 1.13  | 230000 | 1.9305          | 19.0855 | 7.6303 | 15.1943 | 17.3942   | 18.9997 |
  | 1.9171        | 1.18  | 240000 | 1.9291          | 19.0711 | 7.6437 | 15.2175 | 17.3893   | 18.9995 |
  | 1.9393        | 1.23  | 250000 | 1.9230          | 19.276  | 7.725  | 15.3826 | 17.586    | 18.9995 |
  | 1.9295        | 1.28  | 260000 | 1.9197          | 19.2999 | 7.7958 | 15.3961 | 17.6056   | 18.9975 |
  | 1.9725        | 1.33  | 270000 | 1.9173          | 19.2958 | 7.7121 | 15.3659 | 17.584    | 19.0    |
  | 1.9668        | 1.38  | 280000 | 1.9129          | 19.089  | 7.6846 | 15.2395 | 17.3879   | 18.9998 |
  | 1.941         | 1.43  | 290000 | 1.9132          | 19.2127 | 7.7336 | 15.311  | 17.4742   | 18.9995 |
  | 1.9427        | 1.48  | 300000 | 1.9108          | 19.217  | 7.7591 | 15.334  | 17.53     | 18.9998 |
  | 1.9521        | 1.53  | 310000 | 1.9041          | 19.1285 | 7.6736 | 15.2625 | 17.458    | 19.0    |
  | 1.9352        | 1.58  | 320000 | 1.9041          | 19.1656 | 7.723  | 15.3035 | 17.4818   | 18.9991 |
  | 