--- license: mit base_model: vicgalle/gpt2-alpaca-gpt4 tags: - generated_from_trainer model-index: - name: gpt2-alpaca-pandalm results: [] --- # gpt2-alpaca-pandalm This model is a fine-tuned version of [vicgalle/gpt2-alpaca-gpt4](https://huggingface.co/vicgalle/gpt2-alpaca-gpt4) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.8219 ## 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: 0.0002 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.03 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:-----:|:---------------:| | No log | 0.0 | 200 | 2.2796 | | No log | 0.01 | 400 | 1.7930 | | No log | 0.01 | 600 | 1.2870 | | No log | 0.01 | 800 | 1.1460 | | No log | 0.01 | 1000 | 1.0742 | | No log | 0.02 | 1200 | 1.0431 | | No log | 0.02 | 1400 | 1.0250 | | No log | 0.02 | 1600 | 1.0108 | | No log | 0.03 | 1800 | 0.9998 | | No log | 0.03 | 2000 | 0.9937 | | No log | 0.03 | 2200 | 0.9791 | | No log | 0.03 | 2400 | 0.9817 | | No log | 0.04 | 2600 | 0.9617 | | No log | 0.04 | 2800 | 0.9580 | | 1.2199 | 0.04 | 3000 | 0.9757 | | 1.2199 | 0.04 | 3200 | 0.9541 | | 1.2199 | 0.05 | 3400 | 0.9548 | | 1.2199 | 0.05 | 3600 | 0.9485 | | 1.2199 | 0.05 | 3800 | 0.9395 | | 1.2199 | 0.06 | 4000 | 0.9413 | | 1.2199 | 0.06 | 4200 | 0.9336 | | 1.2199 | 0.06 | 4400 | 0.9369 | | 1.2199 | 0.06 | 4600 | 0.9346 | | 1.2199 | 0.07 | 4800 | 0.9277 | | 1.2199 | 0.07 | 5000 | 0.9255 | | 1.2199 | 0.07 | 5200 | 0.9253 | | 1.2199 | 0.08 | 5400 | 0.9152 | | 1.2199 | 0.08 | 5600 | 0.9203 | | 1.2199 | 0.08 | 5800 | 0.9244 | | 0.9222 | 0.08 | 6000 | 0.9178 | | 0.9222 | 0.09 | 6200 | 0.9230 | | 0.9222 | 0.09 | 6400 | 0.9109 | | 0.9222 | 0.09 | 6600 | 0.9132 | | 0.9222 | 0.09 | 6800 | 0.9159 | | 0.9222 | 0.1 | 7000 | 0.9090 | | 0.9222 | 0.1 | 7200 | 0.9073 | | 0.9222 | 0.1 | 7400 | 0.9115 | | 0.9222 | 0.11 | 7600 | 0.9125 | | 0.9222 | 0.11 | 7800 | 0.9087 | | 0.9222 | 0.11 | 8000 | 0.9103 | | 0.9222 | 0.11 | 8200 | 0.9061 | | 0.9222 | 0.12 | 8400 | 0.9047 | | 0.9222 | 0.12 | 8600 | 0.9025 | | 0.9222 | 0.12 | 8800 | 0.9023 | | 0.8883 | 0.13 | 9000 | 0.8949 | | 0.8883 | 0.13 | 9200 | 0.8939 | | 0.8883 | 0.13 | 9400 | 0.8942 | | 0.8883 | 0.13 | 9600 | 0.8993 | | 0.8883 | 0.14 | 9800 | 0.8925 | | 0.8883 | 0.14 | 10000 | 0.8891 | | 0.8883 | 0.14 | 10200 | 0.8874 | | 0.8883 | 0.15 | 10400 | 0.8941 | | 0.8883 | 0.15 | 10600 | 0.8905 | | 0.8883 | 0.15 | 10800 | 0.8863 | | 0.8883 | 0.15 | 11000 | 0.8916 | | 0.8883 | 0.16 | 11200 | 0.8902 | | 0.8883 | 0.16 | 11400 | 0.8851 | | 0.8883 | 0.16 | 11600 | 0.8832 | | 0.8883 | 0.16 | 11800 | 0.8824 | | 0.8719 | 0.17 | 12000 | 0.8793 | | 0.8719 | 0.17 | 12200 | 0.8797 | | 0.8719 | 0.17 | 12400 | 0.8810 | | 0.8719 | 0.18 | 12600 | 0.8796 | | 0.8719 | 0.18 | 12800 | 0.8749 | | 0.8719 | 0.18 | 13000 | 0.8740 | | 0.8719 | 0.18 | 13200 | 0.8757 | | 0.8719 | 0.19 | 13400 | 0.8767 | | 0.8719 | 0.19 | 13600 | 0.8778 | | 0.8719 | 0.19 | 13800 | 0.8793 | | 0.8719 | 0.2 | 14000 | 0.8776 | | 0.8719 | 0.2 | 14200 | 0.8740 | | 0.8719 | 0.2 | 14400 | 0.8731 | | 0.8719 | 0.2 | 14600 | 0.8729 | | 0.8719 | 0.21 | 14800 | 0.8733 | | 0.8605 | 0.21 | 15000 | 0.8739 | | 0.8605 | 0.21 | 15200 | 0.8669 | | 0.8605 | 0.21 | 15400 | 0.8629 | | 0.8605 | 0.22 | 15600 | 0.8673 | | 0.8605 | 0.22 | 15800 | 0.8653 | | 0.8605 | 0.22 | 16000 | 0.8703 | | 0.8605 | 0.23 | 16200 | 0.8685 | | 0.8605 | 0.23 | 16400 | 0.8693 | | 0.8605 | 0.23 | 16600 | 0.8684 | | 0.8605 | 0.23 | 16800 | 0.8629 | | 0.8605 | 0.24 | 17000 | 0.8643 | | 0.8605 | 0.24 | 17200 | 0.8625 | | 0.8605 | 0.24 | 17400 | 0.8604 | | 0.8605 | 0.25 | 17600 | 0.8599 | | 0.8605 | 0.25 | 17800 | 0.8617 | | 0.8537 | 0.25 | 18000 | 0.8618 | | 0.8537 | 0.25 | 18200 | 0.8608 | | 0.8537 | 0.26 | 18400 | 0.8626 | | 0.8537 | 0.26 | 18600 | 0.8607 | | 0.8537 | 0.26 | 18800 | 0.8577 | | 0.8537 | 0.26 | 19000 | 0.8584 | | 0.8537 | 0.27 | 19200 | 0.8597 | | 0.8537 | 0.27 | 19400 | 0.8561 | | 0.8537 | 0.27 | 19600 | 0.8578 | | 0.8537 | 0.28 | 19800 | 0.8545 | | 0.8537 | 0.28 | 20000 | 0.8539 | | 0.8537 | 0.28 | 20200 | 0.8578 | | 0.8537 | 0.28 | 20400 | 0.8536 | | 0.8537 | 0.29 | 20600 | 0.8527 | | 0.8537 | 0.29 | 20800 | 0.8551 | | 0.8472 | 0.29 | 21000 | 0.8542 | | 0.8472 | 0.3 | 21200 | 0.8547 | | 0.8472 | 0.3 | 21400 | 0.8528 | | 0.8472 | 0.3 | 21600 | 0.8540 | | 0.8472 | 0.3 | 21800 | 0.8503 | | 0.8472 | 0.31 | 22000 | 0.8498 | | 0.8472 | 0.31 | 22200 | 0.8502 | | 0.8472 | 0.31 | 22400 | 0.8522 | | 0.8472 | 0.32 | 22600 | 0.8499 | | 0.8472 | 0.32 | 22800 | 0.8511 | | 0.8472 | 0.32 | 23000 | 0.8503 | | 0.8472 | 0.32 | 23200 | 0.8498 | | 0.8472 | 0.33 | 23400 | 0.8463 | | 0.8472 | 0.33 | 23600 | 0.8488 | | 0.8472 | 0.33 | 23800 | 0.8510 | | 0.8421 | 0.33 | 24000 | 0.8479 | | 0.8421 | 0.34 | 24200 | 0.8486 | | 0.8421 | 0.34 | 24400 | 0.8485 | | 0.8421 | 0.34 | 24600 | 0.8484 | | 0.8421 | 0.35 | 24800 | 0.8495 | | 0.8421 | 0.35 | 25000 | 0.8475 | | 0.8421 | 0.35 | 25200 | 0.8484 | | 0.8421 | 0.35 | 25400 | 0.8479 | | 0.8421 | 0.36 | 25600 | 0.8479 | | 0.8421 | 0.36 | 25800 | 0.8452 | | 0.8421 | 0.36 | 26000 | 0.8481 | | 0.8421 | 0.37 | 26200 | 0.8479 | | 0.8421 | 0.37 | 26400 | 0.8442 | | 0.8421 | 0.37 | 26600 | 0.8441 | | 0.8421 | 0.37 | 26800 | 0.8440 | | 0.8377 | 0.38 | 27000 | 0.8412 | | 0.8377 | 0.38 | 27200 | 0.8421 | | 0.8377 | 0.38 | 27400 | 0.8432 | | 0.8377 | 0.38 | 27600 | 0.8425 | | 0.8377 | 0.39 | 27800 | 0.8432 | | 0.8377 | 0.39 | 28000 | 0.8432 | | 0.8377 | 0.39 | 28200 | 0.8421 | | 0.8377 | 0.4 | 28400 | 0.8435 | | 0.8377 | 0.4 | 28600 | 0.8432 | | 0.8377 | 0.4 | 28800 | 0.8417 | | 0.8377 | 0.4 | 29000 | 0.8403 | | 0.8377 | 0.41 | 29200 | 0.8444 | | 0.8377 | 0.41 | 29400 | 0.8425 | | 0.8377 | 0.41 | 29600 | 0.8422 | | 0.8377 | 0.42 | 29800 | 0.8438 | | 0.8291 | 0.42 | 30000 | 0.8399 | | 0.8291 | 0.42 | 30200 | 0.8450 | | 0.8291 | 0.42 | 30400 | 0.8421 | | 0.8291 | 0.43 | 30600 | 0.8402 | | 0.8291 | 0.43 | 30800 | 0.8441 | | 0.8291 | 0.43 | 31000 | 0.8418 | | 0.8291 | 0.44 | 31200 | 0.8422 | | 0.8291 | 0.44 | 31400 | 0.8376 | | 0.8291 | 0.44 | 31600 | 0.8386 | | 0.8291 | 0.44 | 31800 | 0.8412 | | 0.8291 | 0.45 | 32000 | 0.8447 | | 0.8291 | 0.45 | 32200 | 0.8428 | | 0.8291 | 0.45 | 32400 | 0.8409 | | 0.8291 | 0.45 | 32600 | 0.8375 | | 0.8291 | 0.46 | 32800 | 0.8354 | | 0.8279 | 0.46 | 33000 | 0.8360 | | 0.8279 | 0.46 | 33200 | 0.8373 | | 0.8279 | 0.47 | 33400 | 0.8372 | | 0.8279 | 0.47 | 33600 | 0.8393 | | 0.8279 | 0.47 | 33800 | 0.8363 | | 0.8279 | 0.47 | 34000 | 0.8370 | | 0.8279 | 0.48 | 34200 | 0.8359 | | 0.8279 | 0.48 | 34400 | 0.8336 | | 0.8279 | 0.48 | 34600 | 0.8334 | | 0.8279 | 0.49 | 34800 | 0.8322 | | 0.8279 | 0.49 | 35000 | 0.8326 | | 0.8279 | 0.49 | 35200 | 0.8315 | | 0.8279 | 0.49 | 35400 | 0.8354 | | 0.8279 | 0.5 | 35600 | 0.8360 | | 0.8279 | 0.5 | 35800 | 0.8321 | | 0.8254 | 0.5 | 36000 | 0.8341 | | 0.8254 | 0.5 | 36200 | 0.8350 | | 0.8254 | 0.51 | 36400 | 0.8344 | | 0.8254 | 0.51 | 36600 | 0.8335 | | 0.8254 | 0.51 | 36800 | 0.8337 | | 0.8254 | 0.52 | 37000 | 0.8305 | | 0.8254 | 0.52 | 37200 | 0.8308 | | 0.8254 | 0.52 | 37400 | 0.8319 | | 0.8254 | 0.52 | 37600 | 0.8320 | | 0.8254 | 0.53 | 37800 | 0.8292 | | 0.8254 | 0.53 | 38000 | 0.8316 | | 0.8254 | 0.53 | 38200 | 0.8329 | | 0.8254 | 0.54 | 38400 | 0.8314 | | 0.8254 | 0.54 | 38600 | 0.8301 | | 0.8254 | 0.54 | 38800 | 0.8319 | | 0.822 | 0.54 | 39000 | 0.8325 | | 0.822 | 0.55 | 39200 | 0.8313 | | 0.822 | 0.55 | 39400 | 0.8305 | | 0.822 | 0.55 | 39600 | 0.8303 | | 0.822 | 0.55 | 39800 | 0.8283 | | 0.822 | 0.56 | 40000 | 0.8315 | | 0.822 | 0.56 | 40200 | 0.8280 | | 0.822 | 0.56 | 40400 | 0.8316 | | 0.822 | 0.57 | 40600 | 0.8303 | | 0.822 | 0.57 | 40800 | 0.8317 | | 0.822 | 0.57 | 41000 | 0.8302 | | 0.822 | 0.57 | 41200 | 0.8298 | | 0.822 | 0.58 | 41400 | 0.8313 | | 0.822 | 0.58 | 41600 | 0.8304 | | 0.822 | 0.58 | 41800 | 0.8289 | | 0.819 | 0.59 | 42000 | 0.8293 | | 0.819 | 0.59 | 42200 | 0.8315 | | 0.819 | 0.59 | 42400 | 0.8250 | | 0.819 | 0.59 | 42600 | 0.8264 | | 0.819 | 0.6 | 42800 | 0.8282 | | 0.819 | 0.6 | 43000 | 0.8290 | | 0.819 | 0.6 | 43200 | 0.8283 | | 0.819 | 0.61 | 43400 | 0.8291 | | 0.819 | 0.61 | 43600 | 0.8271 | | 0.819 | 0.61 | 43800 | 0.8261 | | 0.819 | 0.61 | 44000 | 0.8276 | | 0.819 | 0.62 | 44200 | 0.8274 | | 0.819 | 0.62 | 44400 | 0.8279 | | 0.819 | 0.62 | 44600 | 0.8264 | | 0.819 | 0.62 | 44800 | 0.8275 | | 0.8203 | 0.63 | 45000 | 0.8266 | | 0.8203 | 0.63 | 45200 | 0.8259 | | 0.8203 | 0.63 | 45400 | 0.8277 | | 0.8203 | 0.64 | 45600 | 0.8269 | | 0.8203 | 0.64 | 45800 | 0.8261 | | 0.8203 | 0.64 | 46000 | 0.8245 | | 0.8203 | 0.64 | 46200 | 0.8243 | | 0.8203 | 0.65 | 46400 | 0.8242 | | 0.8203 | 0.65 | 46600 | 0.8244 | | 0.8203 | 0.65 | 46800 | 0.8237 | | 0.8203 | 0.66 | 47000 | 0.8247 | | 0.8203 | 0.66 | 47200 | 0.8238 | | 0.8203 | 0.66 | 47400 | 0.8239 | | 0.8203 | 0.66 | 47600 | 0.8252 | | 0.8203 | 0.67 | 47800 | 0.8267 | | 0.8169 | 0.67 | 48000 | 0.8245 | | 0.8169 | 0.67 | 48200 | 0.8251 | | 0.8169 | 0.67 | 48400 | 0.8247 | | 0.8169 | 0.68 | 48600 | 0.8252 | | 0.8169 | 0.68 | 48800 | 0.8259 | | 0.8169 | 0.68 | 49000 | 0.8244 | | 0.8169 | 0.69 | 49200 | 0.8245 | | 0.8169 | 0.69 | 49400 | 0.8260 | | 0.8169 | 0.69 | 49600 | 0.8265 | | 0.8169 | 0.69 | 49800 | 0.8258 | | 0.8169 | 0.7 | 50000 | 0.8274 | | 0.8169 | 0.7 | 50200 | 0.8287 | | 0.8169 | 0.7 | 50400 | 0.8280 | | 0.8169 | 0.71 | 50600 | 0.8266 | | 0.8169 | 0.71 | 50800 | 0.8259 | | 0.8153 | 0.71 | 51000 | 0.8263 | | 0.8153 | 0.71 | 51200 | 0.8260 | | 0.8153 | 0.72 | 51400 | 0.8258 | | 0.8153 | 0.72 | 51600 | 0.8251 | | 0.8153 | 0.72 | 51800 | 0.8250 | | 0.8153 | 0.73 | 52000 | 0.8254 | | 0.8153 | 0.73 | 52200 | 0.8244 | | 0.8153 | 0.73 | 52400 | 0.8236 | | 0.8153 | 0.73 | 52600 | 0.8234 | | 0.8153 | 0.74 | 52800 | 0.8251 | | 0.8153 | 0.74 | 53000 | 0.8246 | | 0.8153 | 0.74 | 53200 | 0.8248 | | 0.8153 | 0.74 | 53400 | 0.8236 | | 0.8153 | 0.75 | 53600 | 0.8243 | | 0.8153 | 0.75 | 53800 | 0.8255 | | 0.8123 | 0.75 | 54000 | 0.8246 | | 0.8123 | 0.76 | 54200 | 0.8235 | | 0.8123 | 0.76 | 54400 | 0.8235 | | 0.8123 | 0.76 | 54600 | 0.8235 | | 0.8123 | 0.76 | 54800 | 0.8238 | | 0.8123 | 0.77 | 55000 | 0.8242 | | 0.8123 | 0.77 | 55200 | 0.8233 | | 0.8123 | 0.77 | 55400 | 0.8236 | | 0.8123 | 0.78 | 55600 | 0.8226 | | 0.8123 | 0.78 | 55800 | 0.8225 | | 0.8123 | 0.78 | 56000 | 0.8220 | | 0.8123 | 0.78 | 56200 | 0.8228 | | 0.8123 | 0.79 | 56400 | 0.8230 | | 0.8123 | 0.79 | 56600 | 0.8226 | | 0.8123 | 0.79 | 56800 | 0.8223 | | 0.8106 | 0.79 | 57000 | 0.8229 | | 0.8106 | 0.8 | 57200 | 0.8225 | | 0.8106 | 0.8 | 57400 | 0.8229 | | 0.8106 | 0.8 | 57600 | 0.8230 | | 0.8106 | 0.81 | 57800 | 0.8234 | | 0.8106 | 0.81 | 58000 | 0.8230 | | 0.8106 | 0.81 | 58200 | 0.8231 | | 0.8106 | 0.81 | 58400 | 0.8227 | | 0.8106 | 0.82 | 58600 | 0.8227 | | 0.8106 | 0.82 | 58800 | 0.8213 | | 0.8106 | 0.82 | 59000 | 0.8209 | | 0.8106 | 0.83 | 59200 | 0.8213 | | 0.8106 | 0.83 | 59400 | 0.8214 | | 0.8106 | 0.83 | 59600 | 0.8219 | | 0.8106 | 0.83 | 59800 | 0.8220 | | 0.813 | 0.84 | 60000 | 0.8214 | | 0.813 | 0.84 | 60200 | 0.8217 | | 0.813 | 0.84 | 60400 | 0.8217 | | 0.813 | 0.85 | 60600 | 0.8221 | | 0.813 | 0.85 | 60800 | 0.8227 | | 0.813 | 0.85 | 61000 | 0.8225 | | 0.813 | 0.85 | 61200 | 0.8226 | | 0.813 | 0.86 | 61400 | 0.8218 | | 0.813 | 0.86 | 61600 | 0.8223 | | 0.813 | 0.86 | 61800 | 0.8229 | | 0.813 | 0.86 | 62000 | 0.8224 | | 0.813 | 0.87 | 62200 | 0.8222 | | 0.813 | 0.87 | 62400 | 0.8222 | | 0.813 | 0.87 | 62600 | 0.8224 | | 0.813 | 0.88 | 62800 | 0.8224 | | 0.8073 | 0.88 | 63000 | 0.8226 | | 0.8073 | 0.88 | 63200 | 0.8222 | | 0.8073 | 0.88 | 63400 | 0.8219 | | 0.8073 | 0.89 | 63600 | 0.8216 | | 0.8073 | 0.89 | 63800 | 0.8214 | | 0.8073 | 0.89 | 64000 | 0.8212 | | 0.8073 | 0.9 | 64200 | 0.8214 | | 0.8073 | 0.9 | 64400 | 0.8216 | | 0.8073 | 0.9 | 64600 | 0.8217 | | 0.8073 | 0.9 | 64800 | 0.8219 | | 0.8073 | 0.91 | 65000 | 0.8217 | | 0.8073 | 0.91 | 65200 | 0.8217 | | 0.8073 | 0.91 | 65400 | 0.8217 | | 0.8073 | 0.91 | 65600 | 0.8219 | | 0.8073 | 0.92 | 65800 | 0.8219 | | 0.8095 | 0.92 | 66000 | 0.8217 | | 0.8095 | 0.92 | 66200 | 0.8218 | | 0.8095 | 0.93 | 66400 | 0.8218 | | 0.8095 | 0.93 | 66600 | 0.8217 | | 0.8095 | 0.93 | 66800 | 0.8217 | | 0.8095 | 0.93 | 67000 | 0.8216 | | 0.8095 | 0.94 | 67200 | 0.8217 | | 0.8095 | 0.94 | 67400 | 0.8218 | | 0.8095 | 0.94 | 67600 | 0.8218 | | 0.8095 | 0.95 | 67800 | 0.8218 | | 0.8095 | 0.95 | 68000 | 0.8217 | | 0.8095 | 0.95 | 68200 | 0.8218 | | 0.8095 | 0.95 | 68400 | 0.8218 | | 0.8095 | 0.96 | 68600 | 0.8219 | | 0.8095 | 0.96 | 68800 | 0.8219 | | 0.8086 | 0.96 | 69000 | 0.8218 | | 0.8086 | 0.96 | 69200 | 0.8218 | | 0.8086 | 0.97 | 69400 | 0.8219 | | 0.8086 | 0.97 | 69600 | 0.8218 | | 0.8086 | 0.97 | 69800 | 0.8219 | | 0.8086 | 0.98 | 70000 | 0.8219 | | 0.8086 | 0.98 | 70200 | 0.8219 | | 0.8086 | 0.98 | 70400 | 0.8219 | | 0.8086 | 0.98 | 70600 | 0.8219 | | 0.8086 | 0.99 | 70800 | 0.8219 | | 0.8086 | 0.99 | 71000 | 0.8219 | | 0.8086 | 0.99 | 71200 | 0.8219 | | 0.8086 | 1.0 | 71400 | 0.8219 | | 0.8086 | 1.0 | 71600 | 0.8219 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.1.2 - Datasets 2.18.0 - Tokenizers 0.13.3