| epochs | train_loss | eval_loss |
| ------ | ---------- | --------- |
| 50     | 4.377000   | 3.628506  |
| 100    | 2.636800   | 2.558457  |
| 150    | 2.428800   | 2.427239  |
| 200    | 2.334800   | 2.193493  |
| 250    | 2.188500   | 2.186310  |
| 300    | 2.112400   | 2.173394  |
| 350    | 2.122900   | 2.163947  |
| 400    | 2.155400   | 2.162106  |
| 450    | 2.072100   | 2.154830  |
| 500    | 1.979900   | 2.165512  |
| 550    | 1.935800   | 2.176313  |
| 600    | 1.942800   | 2.170668  |
| 650    | 1.968000   | 2.162810  |
| 700    | 1.974100   | 2.167501  |
| 750    | 1.801900   | 2.235841  |
| 800    | 1.768000   | 2.233753  |
| 850    | 1.779100   | 2.218278  |
| 900    | 1.828900   | 2.220891  |
| 950    | 1.854900   | 2.208387  |
| 1000   | 1.653600   | 2.302763  |
| 1050   | 1.663500   | 2.307982  |
| 1100   | 1.673400   | 2.301423  |
| 1150   | 1.608400   | 2.320958  |
| 1200   | 1.683500   | 2.303580  |
| 1250   | 1.532100   | 2.434277  |
| 1300   | 1.558900   | 2.418276  |
| 1350   | 1.508900   | 2.422347  |
| 1400   | 1.535100   | 2.416650  |
| 1450   | 1.529900   | 2.415497  |