End of training

README.md

@@ -15,12 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on the None dataset.
 It achieves the following results on the evaluation set:
-- eval_loss: 3.6518
-- eval_runtime: 182.7237
-- eval_samples_per_second: 144.256
-- eval_steps_per_second: 18.033
-- epoch: 0.34
-- step: 4500
+- Loss: 3.7706
 
 ## Model description
 
@@ -45,11 +40,40 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 100
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss |
+|:-------------:|:-----:|:-----:|:---------------:|
+| 4.0085        | 0.13  | 500   | 3.8586          |
+| 3.9418        | 0.25  | 1000  | 3.8368          |
+| 3.9257        | 0.38  | 1500  | 3.8236          |
+| 3.9012        | 0.51  | 2000  | 3.8139          |
+| 3.9131        | 0.63  | 2500  | 3.8052          |
+| 3.8947        | 0.76  | 3000  | 3.7976          |
+| 3.8943        | 0.88  | 3500  | 3.7912          |
+| 3.8809        | 1.01  | 4000  | 3.7887          |
+| 3.8243        | 1.14  | 4500  | 3.7877          |
+| 3.8251        | 1.26  | 5000  | 3.7854          |
+| 3.822         | 1.39  | 5500  | 3.7824          |
+| 3.8141        | 1.52  | 6000  | 3.7808          |
+| 3.8243        | 1.64  | 6500  | 3.7785          |
+| 3.8108        | 1.77  | 7000  | 3.7762          |
+| 3.8059        | 1.89  | 7500  | 3.7755          |
+| 3.7984        | 2.02  | 8000  | 3.7765          |
+| 3.7866        | 2.15  | 8500  | 3.7747          |
+| 3.7761        | 2.27  | 9000  | 3.7746          |
+| 3.7764        | 2.4   | 9500  | 3.7727          |
+| 3.779         | 2.53  | 10000 | 3.7727          |
+| 3.7744        | 2.65  | 10500 | 3.7719          |
+| 3.7685        | 2.78  | 11000 | 3.7708          |
+| 3.7694        | 2.9   | 11500 | 3.7706          |
+
 
 ### Framework versions
 
 - Transformers 4.35.2
 - Pytorch 2.1.0+cu121
-- Datasets 2.15.0
+- Datasets 2.16.1
 - Tokenizers 0.15.0

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