training completed[dev]: 512 128

README.md

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+---
+license: apache-2.0
+base_model: t5-base
+tags:
+- generated_from_trainer
+metrics:
+- rouge
+- wer
+model-index:
+- name: t-5-base-baseline
+  results: []
+---
+
+<!-- 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. -->
+
+# t-5-base-baseline
+
+This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1785
+- Rouge1: 0.6774
+- Rouge2: 0.4106
+- Rougel: 0.6163
+- Rougelsum: 0.6162
+- Wer: 0.4869
+- Bleurt: 0.3779
+
+## 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: 6
+- eval_batch_size: 6
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Wer    | Bleurt |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:------:|:------:|
+| No log        | 0.13  | 250  | 1.3316          | 0.651  | 0.3769 | 0.5867 | 0.5868    | 0.5217 | 0.3009 |
+| 1.7919        | 0.27  | 500  | 1.2776          | 0.6595 | 0.3865 | 0.5963 | 0.5963    | 0.5108 | 0.3009 |
+| 1.7919        | 0.4   | 750  | 1.2513          | 0.6635 | 0.393  | 0.6015 | 0.6016    | 0.5039 | 0.3009 |
+| 1.3552        | 0.53  | 1000 | 1.2326          | 0.6668 | 0.3967 | 0.6049 | 0.6049    | 0.5008 | 0.3009 |
+| 1.3552        | 0.66  | 1250 | 1.2236          | 0.6692 | 0.4    | 0.6073 | 0.6073    | 0.4972 | 0.3314 |
+| 1.3074        | 0.8   | 1500 | 1.2118          | 0.6713 | 0.4022 | 0.6094 | 0.6094    | 0.4953 | 0.3314 |
+| 1.3074        | 0.93  | 1750 | 1.2022          | 0.6715 | 0.4035 | 0.6106 | 0.6106    | 0.4932 | 0.2798 |
+| 1.3037        | 1.06  | 2000 | 1.1972          | 0.6731 | 0.4053 | 0.6118 | 0.6118    | 0.4916 | 0.3771 |
+| 1.3037        | 1.2   | 2250 | 1.1909          | 0.675  | 0.4068 | 0.6137 | 0.6136    | 0.4905 | 0.3314 |
+| 1.2676        | 1.33  | 2500 | 1.1889          | 0.6761 | 0.4087 | 0.6144 | 0.6144    | 0.4893 | 0.3314 |
+| 1.2676        | 1.46  | 2750 | 1.1848          | 0.6763 | 0.4091 | 0.6151 | 0.6151    | 0.4884 | 0.3314 |
+| 1.2796        | 1.6   | 3000 | 1.1829          | 0.6771 | 0.4095 | 0.6155 | 0.6155    | 0.488  | 0.3123 |
+| 1.2796        | 1.73  | 3250 | 1.1808          | 0.6769 | 0.4101 | 0.6159 | 0.6159    | 0.4876 | 0.3779 |
+| 1.2489        | 1.86  | 3500 | 1.1787          | 0.6772 | 0.4105 | 0.6162 | 0.6162    | 0.4869 | 0.3771 |
+| 1.2489        | 1.99  | 3750 | 1.1785          | 0.6774 | 0.4106 | 0.6163 | 0.6162    | 0.4869 | 0.3779 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

all_results.json

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+{
+    "test_BLEURT": -0.9706,
+    "test_WER": 0.4816,
+    "test_loss": 1.195426344871521,
+    "test_rouge1": 0.6823,
+    "test_rouge2": 0.4189,
+    "test_rougeL": 0.6225,
+    "test_rougeLsum": 0.6219,
+    "test_runtime": 31.876,
+    "test_samples_per_second": 11.827,
+    "test_steps_per_second": 1.976
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "decoder_start_token_id": 0,
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.38.2"
+}

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 size 891644712

runs/Mar30_02-19-53_9404495fcefe/events.out.tfevents.1711765198.9404495fcefe.1247.0

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+size 15967

test_results.json

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+{
+    "test_BLEURT": -0.9706,
+    "test_WER": 0.4816,
+    "test_loss": 1.195426344871521,
+    "test_rouge1": 0.6823,
+    "test_rouge2": 0.4189,
+    "test_rougeL": 0.6225,
+    "test_rougeLsum": 0.6219,
+    "test_runtime": 31.876,
+    "test_samples_per_second": 11.827,
+    "test_steps_per_second": 1.976
+}