Model save

README.md

@@ -0,0 +1,80 @@
+---
+base_model: aubmindlab/aragpt2-base
+tags:
+- generated_from_trainer
+metrics:
+- bleu
+- rouge
+model-index:
+- name: res_nw_irq_aragpt2-base
+  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. -->
+
+# res_nw_irq_aragpt2-base
+
+This model is a fine-tuned version of [aubmindlab/aragpt2-base](https://huggingface.co/aubmindlab/aragpt2-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2191
+- Bleu: 0.0944
+- Rouge1: 0.4103
+- Rouge2: 0.1839
+- Rougel: 0.4066
+
+## 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
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 20.0
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Bleu   | Rouge1 | Rouge2 | Rougel |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:------:|
+| 0.9334        | 1.0   | 1057  | 0.2461          | 0.0032 | 0.1593 | 0.0185 | 0.1533 |
+| 0.0868        | 2.0   | 2114  | 0.2332          | 0.0149 | 0.2455 | 0.0510 | 0.2394 |
+| 0.0767        | 3.0   | 3171  | 0.2342          | 0.0252 | 0.2961 | 0.0782 | 0.2910 |
+| 0.0696        | 4.0   | 4228  | 0.2278          | 0.0404 | 0.3300 | 0.1050 | 0.3252 |
+| 0.0636        | 5.0   | 5285  | 0.2219          | 0.0517 | 0.3536 | 0.1215 | 0.3480 |
+| 0.0587        | 6.0   | 6342  | 0.2237          | 0.0590 | 0.3654 | 0.1348 | 0.3611 |
+| 0.0542        | 7.0   | 7399  | 0.2194          | 0.0667 | 0.3755 | 0.1440 | 0.3712 |
+| 0.0502        | 8.0   | 8456  | 0.2080          | 0.0715 | 0.3802 | 0.1521 | 0.3761 |
+| 0.0468        | 9.0   | 9513  | 0.2123          | 0.0770 | 0.3931 | 0.1616 | 0.3889 |
+| 0.0438        | 10.0  | 10570 | 0.2112          | 0.0812 | 0.3921 | 0.1648 | 0.3884 |
+| 0.0408        | 11.0  | 11627 | 0.2102          | 0.0816 | 0.3967 | 0.1653 | 0.3936 |
+| 0.0384        | 12.0  | 12684 | 0.2078          | 0.0845 | 0.4018 | 0.1711 | 0.3978 |
+| 0.0363        | 13.0  | 13741 | 0.2145          | 0.0870 | 0.4023 | 0.1720 | 0.3986 |
+| 0.0343        | 14.0  | 14798 | 0.2165          | 0.0878 | 0.4063 | 0.1757 | 0.4023 |
+| 0.0327        | 15.0  | 15855 | 0.2169          | 0.0920 | 0.4049 | 0.1792 | 0.4014 |
+| 0.0313        | 16.0  | 16912 | 0.2175          | 0.0920 | 0.4078 | 0.1821 | 0.4048 |
+| 0.0301        | 17.0  | 17969 | 0.2191          | 0.0944 | 0.4103 | 0.1839 | 0.4066 |
+
+
+### Framework versions
+
+- Transformers 4.45.0.dev0
+- Pytorch 2.3.1+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

egy_training_log.txt

@@ -308,3 +308,5 @@ INFO:root:Epoch 15.0: Train Loss = 0.0343, Eval Loss = 0.21651192009449005
 INFO:absl:Using default tokenizer.
 INFO:root:Epoch 16.0: Train Loss = 0.0327, Eval Loss = 0.21689023077487946
 INFO:absl:Using default tokenizer.
+INFO:root:Epoch 17.0: Train Loss = 0.0313, Eval Loss = 0.21753403544425964
+INFO:absl:Using default tokenizer.

generation_config.json

@@ -0,0 +1,6 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "eos_token_id": 0,
+  "transformers_version": "4.45.0.dev0"
+}

model.safetensors

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 size 540004992