End of training

README.md

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+---
+license: mit
+base_model: alexdg19/bert_large_cnn_daily
+tags:
+- generated_from_trainer
+datasets:
+- cnn_dailymail
+metrics:
+- rouge
+model-index:
+- name: bert_large_cnn_daily2
+  results:
+  - task:
+      name: Sequence-to-sequence Language Modeling
+      type: text2text-generation
+    dataset:
+      name: cnn_dailymail
+      type: cnn_dailymail
+      config: 3.0.0
+      split: test
+      args: 3.0.0
+    metrics:
+    - name: Rouge1
+      type: rouge
+      value: 0.4504
+---
+
+<!-- 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_cnn_daily2
+
+This model is a fine-tuned version of [alexdg19/bert_large_cnn_daily](https://huggingface.co/alexdg19/bert_large_cnn_daily) on the cnn_dailymail dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3008
+- Rouge1: 0.4504
+- Rouge2: 0.2337
+- Rougel: 0.3294
+- Rougelsum: 0.424
+- Gen Len: 60.2728
+
+## 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: 3
+- eval_batch_size: 3
+- seed: 42
+- gradient_accumulation_steps: 3
+- total_train_batch_size: 9
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
+| 1.1882        | 1.0   | 1021 | 1.1904          | 0.4379 | 0.223  | 0.318  | 0.41      | 61.3551 |
+| 0.9513        | 2.0   | 2042 | 1.1891          | 0.4506 | 0.2353 | 0.3312 | 0.4239    | 59.6771 |
+| 0.7581        | 3.0   | 3064 | 1.2440          | 0.4488 | 0.2317 | 0.3273 | 0.4214    | 59.9909 |
+| 0.6364        | 4.0   | 4084 | 1.3008          | 0.4504 | 0.2337 | 0.3294 | 0.424     | 60.2728 |
+
+
+### 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/Nov13_19-56-10_5ea2e3d76cdd/events.out.tfevents.1699905377.5ea2e3d76cdd.1137.0

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