End of training

README.md

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+---
+license: mit
+base_model: alexdg19/bert_large_xsum_samsum
+tags:
+- generated_from_trainer
+datasets:
+- samsum
+metrics:
+- rouge
+model-index:
+- name: bert_large_xsum_samsum3
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: samsum
+      type: samsum
+      config: samsum
+      split: test
+      args: samsum
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 0.5313
+---
+
+<!-- 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. -->
+
+# bert_large_xsum_samsum3
+
+This model is a fine-tuned version of [alexdg19/bert_large_xsum_samsum](https://huggingface.co/alexdg19/bert_large_xsum_samsum) on the samsum dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.2354
+- Rouge1: 0.5313
+- Rouge2: 0.2827
+- Rougel: 0.4367
+- Rougelsum: 0.4357
+- Gen Len: 30.939
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
+| No log        | 1.0   | 164  | 1.1370          | 0.5599 | 0.3246 | 0.4748 | 0.4743    | 29.0122 |
+| No log        | 2.0   | 328  | 1.2659          | 0.5494 | 0.3033 | 0.4623 | 0.4612    | 27.0671 |
+| No log        | 3.0   | 492  | 1.4188          | 0.5198 | 0.2726 | 0.436  | 0.4346    | 28.6768 |
+| 0.6603        | 4.0   | 656  | 1.5628          | 0.5391 | 0.2905 | 0.4555 | 0.4553    | 28.6159 |
+| 0.6603        | 5.0   | 820  | 1.9045          | 0.5237 | 0.2774 | 0.4326 | 0.4321    | 31.5854 |
+| 0.6603        | 6.0   | 984  | 2.0670          | 0.5199 | 0.2689 | 0.4251 | 0.4243    | 31.8049 |
+| 0.1722        | 7.0   | 1148 | 1.9653          | 0.5269 | 0.2703 | 0.4342 | 0.4333    | 28.5122 |
+| 0.1722        | 8.0   | 1312 | 2.1921          | 0.5296 | 0.2765 | 0.4393 | 0.4387    | 31.8354 |
+| 0.1722        | 9.0   | 1476 | 2.4336          | 0.5299 | 0.2825 | 0.4399 | 0.4388    | 31.7988 |
+| 0.052         | 10.0  | 1640 | 2.2354          | 0.5313 | 0.2827 | 0.4367 | 0.4357    | 30.939  |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

generation_config.json

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+{
+  "bos_token_id": 0,
+  "decoder_start_token_id": 2,
+  "early_stopping": true,
+  "eos_token_id": 2,
+  "forced_eos_token_id": 2,
+  "max_length": 62,
+  "min_length": 11,
+  "no_repeat_ngram_size": 3,
+  "num_beams": 6,
+  "pad_token_id": 1,
+  "transformers_version": "4.35.0"
+}

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runs/Nov07_22-56-48_98244a879ce7/events.out.tfevents.1699397815.98244a879ce7.409.0

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