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qing-yao
Available on FriendliAI
Run this model inference on single tenant GPU with unmatched speed and reliability at scale.
Model Details
Model Provider
qing-yao
Model Tree
EleutherAI/pythia-160m
Input Modalities
Output Modalities
Supported Functionality
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 10.2523 | 0.005 | 50 | 8.5577 |
| 7.7790 | 0.01 | 100 | 7.5117 |
| 7.2180 | 0.015 | 150 | 7.0027 |
| 6.7753 | 0.02 | 200 | 6.6477 |
| 6.4863 |
| 0.025 |
| 250 |
| 6.4050 |
| 6.2833 | 0.03 | 300 | 6.2509 |
| 6.1096 | 0.035 | 350 | 6.0381 |
| 5.9186 | 0.04 | 400 | 5.8691 |
| 5.7952 | 0.045 | 450 | 5.7315 |
| 5.6755 | 0.05 | 500 | 5.6078 |
| 5.7582 | 0.055 | 550 | 5.9850 |
| 5.6505 | 0.06 | 600 | 5.5307 |
| 5.4548 | 0.065 | 650 | 5.4353 |
| 5.3749 | 0.07 | 700 | 5.3216 |
| 5.2756 | 0.075 | 750 | 5.2574 |
| 5.2141 | 0.08 | 800 | 5.1767 |
| 5.1416 | 0.085 | 850 | 5.1159 |
| 5.0830 | 0.09 | 900 | 5.0741 |
| 5.0291 | 0.095 | 950 | 4.9910 |
| 5.0162 | 0.1 | 1000 | 4.9417 |
| 4.9316 | 0.105 | 1050 | 4.8985 |
| 4.8505 | 0.11 | 1100 | 4.8243 |
| 4.7823 | 0.115 | 1150 | 4.7719 |
| 4.7378 | 0.12 | 1200 | 4.7218 |
| 4.7056 | 0.125 | 1250 | 4.7067 |
| 4.6779 | 0.13 | 1300 | 4.6432 |
| 4.7135 | 0.135 | 1350 | 4.6549 |
| 4.6236 | 0.14 | 1400 | 4.5890 |
| 4.5926 | 0.145 | 1450 | 4.5868 |
| 4.5768 | 0.15 | 1500 | 4.5195 |
| 4.5325 | 0.155 | 1550 | 4.4928 |
| 4.4865 | 0.16 | 1600 | 4.4715 |
| 4.4945 | 0.165 | 1650 | 4.4550 |
| 4.4703 | 0.17 | 1700 | 4.4249 |
| 4.4383 | 0.175 | 1750 | 4.4278 |
| 4.4346 | 0.18 | 1800 | 4.4193 |
| 4.3959 | 0.185 | 1850 | 4.4095 |
| 4.3844 | 0.19 | 1900 | 4.3593 |
| 4.3696 | 0.195 | 1950 | 4.3300 |
| 4.3397 | 0.2 | 2000 | 4.3112 |
| 4.3289 | 0.205 | 2050 | 4.2887 |
| 4.3162 | 0.21 | 2100 | 4.2664 |
| 4.2950 | 0.215 | 2150 | 4.2584 |
| 4.2910 | 0.22 | 2200 | 4.2670 |
| 4.2773 | 0.225 | 2250 | 4.2389 |
| 4.2647 | 0.23 | 2300 | 4.2193 |
| 4.2633 | 0.235 | 2350 | 4.2109 |
| 4.2665 | 0.24 | 2400 | 4.2082 |
| 4.2140 | 0.245 | 2450 | 4.2005 |
| 4.2563 | 0.25 | 2500 | 4.2119 |
| 4.2324 | 0.255 | 2550 | 4.1841 |
| 4.1851 | 0.26 | 2600 | 4.1678 |
| 4.1844 | 0.265 | 2650 | 4.1525 |
| 4.1793 | 0.27 | 2700 | 4.1466 |
| 4.1642 | 0.275 | 2750 | 4.1377 |
| 4.1662 | 0.28 | 2800 | 4.1359 |
| 4.1432 | 0.285 | 2850 | 4.1242 |
| 4.1426 | 0.29 | 2900 | 4.1206 |
| 4.1075 | 0.295 | 2950 | 4.1101 |
| 4.1448 | 0.3 | 3000 | 4.0922 |
| 4.1104 | 0.305 | 3050 | 4.1287 |
| 4.1336 | 0.31 | 3100 | 4.1237 |
| 4.1386 | 0.315 | 3150 | 4.0848 |
| 4.1050 | 0.32 | 3200 | 4.0605 |
| 4.0862 | 0.325 | 3250 | 4.0728 |
| 4.1081 | 0.33 | 3300 | 4.0509 |
| 4.0790 | 0.335 | 3350 | 4.0459 |
| 4.0970 | 0.34 | 3400 | 4.0278 |
| 4.0741 | 0.345 | 3450 | 4.0167 |
| 4.0591 | 0.35 | 3500 | 4.0098 |
| 4.0432 | 0.355 | 3550 | 4.0143 |
| 4.0417 | 0.36 | 3600 | 4.0245 |
| 4.0670 | 0.365 | 3650 | 4.0268 |
| 4.0401 | 0.37 | 3700 | 4.0036 |
| 4.0832 | 0.375 | 3750 | 4.0191 |
| 4.1057 | 0.38 | 3800 | 4.0380 |
| 4.0440 | 0.385 | 3850 | 4.0224 |
| 4.0394 | 0.39 | 3900 | 4.0001 |
| 4.0633 | 0.395 | 3950 | 4.0031 |
| 4.0025 | 0.4 | 4000 | 3.9801 |
| 4.0043 | 0.405 | 4050 | 3.9715 |
| 4.0084 | 0.41 | 4100 | 3.9590 |
| 3.9683 | 0.415 | 4150 | 3.9544 |
| 3.9750 | 0.42 | 4200 | 3.9591 |
| 3.9829 | 0.425 | 4250 | 3.9486 |
| 3.9596 | 0.43 | 4300 | 3.9439 |
| 3.9690 | 0.435 | 4350 | 3.9441 |
| 3.9698 | 0.44 | 4400 | 3.9647 |
| 3.9801 | 0.445 | 4450 | 3.9388 |
| 3.9711 | 0.45 | 4500 | 3.9298 |
| 3.9299 | 0.455 | 4550 | 3.9320 |
| 3.9348 | 0.46 | 4600 | 3.9211 |
| 3.9513 | 0.465 | 4650 | 3.9120 |
| 3.9461 | 0.47 | 4700 | 3.9105 |
| 3.9305 | 0.475 | 4750 | 3.9015 |
| 3.9269 | 0.48 | 4800 | 3.8970 |
| 3.9343 | 0.485 | 4850 | 3.8988 |
| 3.9313 | 0.49 | 4900 | 3.8927 |
| 3.9123 | 0.495 | 4950 | 3.8873 |
| 3.9076 | 0.5 | 5000 | 3.9043 |
| 3.9460 | 0.505 | 5050 | 3.8870 |
| 3.9336 | 0.51 | 5100 | 3.8799 |
| 3.9174 | 0.515 | 5150 | 3.8880 |
| 3.9105 | 0.52 | 5200 | 3.8765 |
| 3.9018 | 0.525 | 5250 | 3.8706 |
| 3.8863 | 0.53 | 5300 | 3.8647 |
| 3.8857 | 0.535 | 5350 | 3.8618 |
| 3.8836 | 0.54 | 5400 | 3.8596 |
| 3.8832 | 0.545 | 5450 | 3.8577 |
| 3.8926 | 0.55 | 5500 | 3.8560 |
| 3.8857 | 0.555 | 5550 | 3.8536 |
| 3.8915 | 0.56 | 5600 | 3.8526 |
| 3.8924 | 0.565 | 5650 | 3.8467 |
| 3.8738 | 0.57 | 5700 | 3.8417 |
| 3.8460 | 0.575 | 5750 | 3.8418 |
| 3.8811 | 0.58 | 5800 | 3.8381 |
| 3.8585 | 0.585 | 5850 | 3.8362 |
| 3.8644 | 0.59 | 5900 | 3.8343 |
| 3.8686 | 0.595 | 5950 | 3.8354 |
| 3.8573 | 0.6 | 6000 | 3.8266 |
| 3.8737 | 0.605 | 6050 | 3.8242 |
| 3.8691 | 0.61 | 6100 | 3.8238 |
| 3.8549 | 0.615 | 6150 | 3.8254 |
| 3.8488 | 0.62 | 6200 | 3.8314 |
| 3.8495 | 0.625 | 6250 | 3.8236 |
| 3.8678 | 0.63 | 6300 | 3.8178 |
| 3.8436 | 0.635 | 6350 | 3.8129 |
| 3.8317 | 0.64 | 6400 | 3.8128 |
| 3.8464 | 0.645 | 6450 | 3.8065 |
| 3.8227 | 0.65 | 6500 | 3.8031 |
| 3.8331 | 0.655 | 6550 | 3.8009 |
| 3.8236 | 0.66 | 6600 | 3.7990 |
| 3.8157 | 0.665 | 6650 | 3.8046 |
| 3.8150 | 0.67 | 6700 | 3.7990 |
| 3.8320 | 0.675 | 6750 | 3.8054 |
| 3.8253 | 0.68 | 6800 | 3.7969 |
| 3.8105 | 0.685 | 6850 | 3.7939 |
| 3.8160 | 0.69 | 6900 | 3.7910 |
| 3.8163 | 0.695 | 6950 | 3.7909 |
| 3.8072 | 0.7 | 7000 | 3.7920 |
| 3.8100 | 0.705 | 7050 | 3.7872 |
| 3.8609 | 0.71 | 7100 | 3.7848 |
| 3.8208 | 0.715 | 7150 | 3.7830 |
| 3.8406 | 0.72 | 7200 | 3.7798 |
| 3.8319 | 0.725 | 7250 | 3.7795 |
| 3.8343 | 0.73 | 7300 | 3.7778 |
| 3.8511 | 0.735 | 7350 | 3.7769 |
| 3.8046 | 0.74 | 7400 | 3.7754 |
| 3.8093 | 0.745 | 7450 | 3.7739 |
| 3.8121 | 0.75 | 7500 | 3.7725 |
| 3.8004 | 0.755 | 7550 | 3.7714 |
| 3.7929 | 0.76 | 7600 | 3.7704 |
| 3.7992 | 0.765 | 7650 | 3.7694 |
| 3.8072 | 0.77 | 7700 | 3.7684 |
| 3.8111 | 0.775 | 7750 | 3.7673 |
| 3.8330 | 0.78 | 7800 | 3.7708 |
| 3.7856 | 0.785 | 7850 | 3.7679 |
| 3.8184 | 0.79 | 7900 | 3.7660 |
| 3.8181 | 0.795 | 7950 | 3.7649 |
| 3.7818 | 0.8 | 8000 | 3.7686 |
| 3.7915 | 0.805 | 8050 | 3.7645 |
| 3.7840 | 0.81 | 8100 | 3.7630 |
| 3.7813 | 0.815 | 8150 | 3.7624 |
| 3.7800 | 0.82 | 8200 | 3.7618 |
| 3.7940 | 0.825 | 8250 | 3.7613 |
| 3.7996 | 0.83 | 8300 | 3.7601 |
| 3.7893 | 0.835 | 8350 | 3.7602 |
| 3.7857 | 0.84 | 8400 | 3.7613 |
| 3.7833 | 0.845 | 8450 | 3.7600 |
| 3.7938 | 0.85 | 8500 | 3.7590 |
| 3.8098 | 0.855 | 8550 | 3.7584 |
| 3.7821 | 0.86 | 8600 | 3.7580 |
| 3.7912 | 0.865 | 8650 | 3.7576 |
| 3.7764 | 0.87 | 8700 | 3.7581 |
| 3.8035 | 0.875 | 8750 | 3.7570 |
| 3.7547 | 0.88 | 8800 | 3.7600 |
| 3.7955 | 0.885 | 8850 | 3.7576 |
| 3.7994 | 0.89 | 8900 | 3.7566 |
| 3.8076 | 0.895 | 8950 | 3.7559 |
| 3.8021 | 0.9 | 9000 | 3.7558 |
| 3.7804 | 0.905 | 9050 | 3.7574 |
| 3.7759 | 0.91 | 9100 | 3.7562 |
| 3.7852 | 0.915 | 9150 | 3.7556 |
| 3.7868 | 0.92 | 9200 | 3.7553 |
| 3.7768 | 0.925 | 9250 | 3.7547 |
| 3.7936 | 0.93 | 9300 | 3.7545 |
| 3.7985 | 0.935 | 9350 | 3.7543 |
| 3.7932 | 0.94 | 9400 | 3.7539 |
| 3.7834 | 0.945 | 9450 | 3.7537 |
| 3.7867 | 0.95 | 9500 | 3.7535 |
| 3.7782 | 0.955 | 9550 | 3.7534 |
| 3.8131 | 0.96 | 9600 | 3.7531 |
| 3.7855 | 0.965 | 9650 | 3.7529 |
| 3.7823 | 0.97 | 9700 | 3.7528 |
| 3.7620 | 0.975 | 9750 | 3.7526 |
| 3.7828 | 0.98 | 9800 | 3.7525 |
| 3.7785 | 0.985 | 9850 | 3.7522 |
| 3.8242 | 0.99 | 9900 | 3.7522 |
| 3.7522 | 0.995 | 9950 | 3.7521 |
| 3.7964 | 1.0 | 10000 | 3.7520 |