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---
license: apache-2.0
base_model: openlm-research/open_llama_3b_v2
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
metrics:
- accuracy
model-index:
- name: openllama-3b-finance
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: financial_phrasebank
type: financial_phrasebank
config: sentences_50agree
split: train
args: sentences_50agree
metrics:
- name: Accuracy
type: accuracy
value: 0.4142561983471074
---
<!-- 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. -->
# openllama-3b-finance
This model is a fine-tuned version of [openlm-research/open_llama_3b_v2](https://huggingface.co/openlm-research/open_llama_3b_v2) on the financial_phrasebank dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9007
- Accuracy: 0.4143
## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 16.4346 | 0.01 | 20 | 2.5105 | 0.4143 |
| 1.8681 | 0.01 | 40 | 5.7312 | 0.4143 |
| 1.8542 | 0.02 | 60 | 5.0027 | 0.4143 |
| 2.3731 | 0.02 | 80 | 4.2958 | 0.4143 |
| 2.3024 | 0.03 | 100 | 4.9771 | 0.4143 |
| 2.6812 | 0.03 | 120 | 4.6762 | 0.4143 |
| 2.4304 | 0.04 | 140 | 5.2389 | 0.4143 |
| 2.561 | 0.04 | 160 | 4.4461 | 0.4143 |
| 2.08 | 0.05 | 180 | 4.6807 | 0.4143 |
| 4.0186 | 0.05 | 200 | 5.3431 | 0.4143 |
| 2.7261 | 0.06 | 220 | 4.9663 | 0.4143 |
| 1.7432 | 0.06 | 240 | 4.4788 | 0.4143 |
| 2.2759 | 0.07 | 260 | 5.6531 | 0.4143 |
| 1.8702 | 0.07 | 280 | 6.7118 | 0.4143 |
| 2.2412 | 0.08 | 300 | 5.0398 | 0.4143 |
| 1.1515 | 0.08 | 320 | 6.3377 | 0.4143 |
| 2.6582 | 0.09 | 340 | 5.0585 | 0.4143 |
| 2.1056 | 0.09 | 360 | 5.6544 | 0.4143 |
| 3.1513 | 0.1 | 380 | 3.8076 | 0.4143 |
| 2.0003 | 0.1 | 400 | 5.1281 | 0.4132 |
| 19.9181 | 0.11 | 420 | 35.4379 | 0.4143 |
| 29.2872 | 0.11 | 440 | 16.2178 | 0.4143 |
| 3.4213 | 0.12 | 460 | 13.0984 | 0.4143 |
| 1.3358 | 0.12 | 480 | 27.2436 | 0.4143 |
| 4.2725 | 0.13 | 500 | 24.0192 | 0.4143 |
| 4.9844 | 0.13 | 520 | 12.9378 | 0.1178 |
| 7.9312 | 0.14 | 540 | 10.8854 | 0.4143 |
| 1.5126 | 0.14 | 560 | 14.3267 | 0.4143 |
| 3.9021 | 0.15 | 580 | 10.0051 | 0.4143 |
| 3.7081 | 0.15 | 600 | 9.5176 | 0.1136 |
| 3.9107 | 0.16 | 620 | 7.2548 | 0.4143 |
| 2.8381 | 0.17 | 640 | 3.9992 | 0.4143 |
| 3.0625 | 0.17 | 660 | 4.3300 | 0.4143 |
| 1.812 | 0.18 | 680 | 10.6038 | 0.4143 |
| 6.9616 | 0.18 | 700 | 11.0092 | 0.4143 |
| 1.7157 | 0.19 | 720 | 14.8428 | 0.4143 |
| 4.7153 | 0.19 | 740 | 3.6624 | 0.4143 |
| 2.8871 | 0.2 | 760 | 5.7465 | 0.4143 |
| 2.4885 | 0.2 | 780 | 12.4440 | 0.4143 |
| 3.137 | 0.21 | 800 | 14.1504 | 0.4143 |
| 3.0503 | 0.21 | 820 | 14.1326 | 0.4143 |
| 2.9254 | 0.22 | 840 | 16.0438 | 0.1291 |
| 2.711 | 0.22 | 860 | 14.0977 | 0.4143 |
| 4.8591 | 0.23 | 880 | 9.3210 | 0.1281 |
| 2.8734 | 0.23 | 900 | 6.3782 | 0.4143 |
| 2.603 | 0.24 | 920 | 5.1658 | 0.4143 |
| 4.4641 | 0.24 | 940 | 3.9345 | 0.4143 |
| 2.3522 | 0.25 | 960 | 5.5901 | 0.1436 |
| 1.9584 | 0.25 | 980 | 5.0562 | 0.4143 |
| 2.679 | 0.26 | 1000 | 2.5428 | 0.4143 |
| 4.13 | 0.26 | 1020 | 1.3911 | 0.4143 |
| 3.4319 | 0.27 | 1040 | 8.2340 | 0.4143 |
| 1.9382 | 0.27 | 1060 | 8.4589 | 0.4143 |
| 2.2712 | 0.28 | 1080 | 6.0251 | 0.4143 |
| 1.8834 | 0.28 | 1100 | 2.4455 | 0.1436 |
| 0.9941 | 0.29 | 1120 | 8.7371 | 0.4143 |
| 3.3895 | 0.29 | 1140 | 6.2867 | 0.1426 |
| 2.2968 | 0.3 | 1160 | 10.3440 | 0.4143 |
| 4.9047 | 0.3 | 1180 | 8.0926 | 0.0816 |
| 4.6894 | 0.31 | 1200 | 3.7347 | 0.3698 |
| 2.9471 | 0.32 | 1220 | 4.9616 | 0.4143 |
| 2.9446 | 0.32 | 1240 | 5.8887 | 0.4143 |
| 1.6756 | 0.33 | 1260 | 7.0233 | 0.4143 |
| 2.0442 | 0.33 | 1280 | 7.5129 | 0.1322 |
| 3.7822 | 0.34 | 1300 | 3.1115 | 0.4143 |
| 2.0277 | 0.34 | 1320 | 5.9831 | 0.4143 |
| 2.624 | 0.35 | 1340 | 3.2104 | 0.4143 |
| 2.1893 | 0.35 | 1360 | 4.3662 | 0.1364 |
| 3.0973 | 0.36 | 1380 | 3.2219 | 0.4143 |
| 1.9835 | 0.36 | 1400 | 5.1431 | 0.4143 |
| 2.9711 | 0.37 | 1420 | 6.0129 | 0.4143 |
| 3.0045 | 0.37 | 1440 | 3.2609 | 0.4143 |
| 1.0503 | 0.38 | 1460 | 7.6840 | 0.4143 |
| 2.5946 | 0.38 | 1480 | 5.1945 | 0.4143 |
| 2.9221 | 0.39 | 1500 | 3.5226 | 0.4143 |
| 1.5624 | 0.39 | 1520 | 5.3887 | 0.4143 |
| 2.0339 | 0.4 | 1540 | 4.2434 | 0.4143 |
| 2.4852 | 0.4 | 1560 | 4.1994 | 0.4143 |
| 1.7668 | 0.41 | 1580 | 5.5635 | 0.4143 |
| 2.282 | 0.41 | 1600 | 5.1922 | 0.4143 |
| 3.2027 | 0.42 | 1620 | 3.9420 | 0.4143 |
| 2.5766 | 0.42 | 1640 | 4.9683 | 0.4143 |
| 2.268 | 0.43 | 1660 | 6.2959 | 0.4143 |
| 3.2091 | 0.43 | 1680 | 4.8009 | 0.4143 |
| 1.9654 | 0.44 | 1700 | 5.8059 | 0.4143 |
| 2.17 | 0.44 | 1720 | 5.4482 | 0.4143 |
| 2.2219 | 0.45 | 1740 | 4.4156 | 0.4143 |
| 1.9873 | 0.45 | 1760 | 5.1548 | 0.4143 |
| 2.51 | 0.46 | 1780 | 3.1345 | 0.4143 |
| 2.8949 | 0.46 | 1800 | 5.3419 | 0.4143 |
| 1.2941 | 0.47 | 1820 | 6.8446 | 0.4143 |
| 2.3475 | 0.48 | 1840 | 5.9935 | 0.4143 |
| 2.7907 | 0.48 | 1860 | 5.8123 | 0.4143 |
| 2.0038 | 0.49 | 1880 | 6.3927 | 0.4143 |
| 2.0324 | 0.49 | 1900 | 6.4023 | 0.4143 |
| 2.3211 | 0.5 | 1920 | 5.9480 | 0.4143 |
| 2.3883 | 0.5 | 1940 | 5.5011 | 0.4143 |
| 2.7683 | 0.51 | 1960 | 3.7333 | 0.4143 |
| 1.6062 | 0.51 | 1980 | 7.2244 | 0.1508 |
| 2.3866 | 0.52 | 2000 | 4.8682 | 0.4143 |
| 2.3527 | 0.52 | 2020 | 3.9189 | 0.4143 |
| 3.0126 | 0.53 | 2040 | 4.3666 | 0.4143 |
| 1.9683 | 0.53 | 2060 | 5.1474 | 0.4143 |
| 2.5018 | 0.54 | 2080 | 4.5417 | 0.4143 |
| 1.555 | 0.54 | 2100 | 5.0804 | 0.4143 |
| 1.6115 | 0.55 | 2120 | 5.1319 | 0.4143 |
| 2.2321 | 0.55 | 2140 | 5.3196 | 0.4143 |
| 2.3614 | 0.56 | 2160 | 4.0629 | 0.4143 |
| 1.6915 | 0.56 | 2180 | 5.8209 | 0.4143 |
| 2.4031 | 0.57 | 2200 | 4.3059 | 0.4143 |
| 1.5659 | 0.57 | 2220 | 5.1369 | 0.4143 |
| 1.2592 | 0.58 | 2240 | 5.4046 | 0.4143 |
| 1.5577 | 0.58 | 2260 | 5.8448 | 0.4143 |
| 1.7656 | 0.59 | 2280 | 5.6683 | 0.4143 |
| 1.5057 | 0.59 | 2300 | 5.7769 | 0.4143 |
| 2.3733 | 0.6 | 2320 | 5.0004 | 0.4143 |
| 2.118 | 0.6 | 2340 | 5.2127 | 0.4143 |
| 2.2942 | 0.61 | 2360 | 4.8589 | 0.4143 |
| 2.0524 | 0.61 | 2380 | 3.9148 | 0.4143 |
| 1.8707 | 0.62 | 2400 | 3.2284 | 0.4143 |
| 1.6804 | 0.62 | 2420 | 4.9466 | 0.4143 |
| 2.5137 | 0.63 | 2440 | 4.5307 | 0.4143 |
| 1.1823 | 0.64 | 2460 | 4.7444 | 0.4143 |
| 2.9106 | 0.64 | 2480 | 3.7200 | 0.4143 |
| 1.3376 | 0.65 | 2500 | 4.6969 | 0.4143 |
| 1.8187 | 0.65 | 2520 | 4.2458 | 0.4143 |
| 1.8444 | 0.66 | 2540 | 4.6003 | 0.4143 |
| 2.1427 | 0.66 | 2560 | 4.7394 | 0.4143 |
| 2.2483 | 0.67 | 2580 | 4.6959 | 0.4143 |
| 1.5997 | 0.67 | 2600 | 5.5665 | 0.4143 |
| 2.0095 | 0.68 | 2620 | 4.5815 | 0.4143 |
| 1.4664 | 0.68 | 2640 | 3.4096 | 0.4143 |
| 1.4128 | 0.69 | 2660 | 4.2751 | 0.4143 |
| 2.4907 | 0.69 | 2680 | 3.0278 | 0.4143 |
| 1.0484 | 0.7 | 2700 | 3.7867 | 0.4143 |
| 2.7561 | 0.7 | 2720 | 4.0402 | 0.4143 |
| 1.2491 | 0.71 | 2740 | 3.3789 | 0.4143 |
| 1.1299 | 0.71 | 2760 | 2.4017 | 0.4143 |
| 1.9811 | 0.72 | 2780 | 3.3625 | 0.4143 |
| 2.1781 | 0.72 | 2800 | 3.2631 | 0.4143 |
| 1.6062 | 0.73 | 2820 | 2.9967 | 0.4143 |
| 0.928 | 0.73 | 2840 | 5.6052 | 0.4143 |
| 2.5659 | 0.74 | 2860 | 4.8605 | 0.4143 |
| 1.4248 | 0.74 | 2880 | 4.8685 | 0.4143 |
| 2.3335 | 0.75 | 2900 | 4.5013 | 0.4143 |
| 1.8546 | 0.75 | 2920 | 3.7017 | 0.4143 |
| 1.5698 | 0.76 | 2940 | 3.8911 | 0.4143 |
| 1.8653 | 0.76 | 2960 | 4.2637 | 0.4143 |
| 1.4354 | 0.77 | 2980 | 5.1895 | 0.4143 |
| 2.0558 | 0.77 | 3000 | 4.4362 | 0.4143 |
| 2.0876 | 0.78 | 3020 | 4.6924 | 0.4143 |
| 2.4282 | 0.78 | 3040 | 4.6526 | 0.4143 |
| 1.4837 | 0.79 | 3060 | 5.2878 | 0.4143 |
| 2.2982 | 0.8 | 3080 | 5.0637 | 0.4143 |
| 2.2615 | 0.8 | 3100 | 4.6995 | 0.4143 |
| 1.7026 | 0.81 | 3120 | 4.4688 | 0.4143 |
| 1.6352 | 0.81 | 3140 | 4.8815 | 0.4143 |
| 2.782 | 0.82 | 3160 | 3.6835 | 0.4143 |
| 0.3105 | 0.82 | 3180 | 3.8391 | 0.4143 |
| 2.3949 | 0.83 | 3200 | 4.9408 | 0.4143 |
| 3.0385 | 0.83 | 3220 | 4.3234 | 0.4143 |
| 2.146 | 0.84 | 3240 | 3.7336 | 0.4143 |
| 1.9198 | 0.84 | 3260 | 4.2217 | 0.4143 |
| 0.7858 | 0.85 | 3280 | 4.4744 | 0.4143 |
| 0.7785 | 0.85 | 3300 | 5.0257 | 0.4143 |
| 2.7858 | 0.86 | 3320 | 4.8552 | 0.4143 |
| 2.0922 | 0.86 | 3340 | 4.2950 | 0.4143 |
| 1.9892 | 0.87 | 3360 | 3.9094 | 0.4143 |
| 2.2241 | 0.87 | 3380 | 3.7403 | 0.4143 |
| 2.7226 | 0.88 | 3400 | 3.6119 | 0.4143 |
| 1.5888 | 0.88 | 3420 | 3.8878 | 0.4143 |
| 2.7581 | 0.89 | 3440 | 4.0297 | 0.4143 |
| 1.5373 | 0.89 | 3460 | 4.0980 | 0.4143 |
| 1.5419 | 0.9 | 3480 | 4.0983 | 0.4143 |
| 1.7618 | 0.9 | 3500 | 4.2322 | 0.4143 |
| 1.8487 | 0.91 | 3520 | 4.3258 | 0.4143 |
| 1.0667 | 0.91 | 3540 | 4.1975 | 0.4143 |
| 2.0457 | 0.92 | 3560 | 4.2679 | 0.4143 |
| 1.8133 | 0.92 | 3580 | 4.1908 | 0.4143 |
| 1.5844 | 0.93 | 3600 | 4.1348 | 0.4143 |
| 1.7202 | 0.93 | 3620 | 4.1382 | 0.4143 |
| 1.7118 | 0.94 | 3640 | 4.1135 | 0.4143 |
| 1.208 | 0.95 | 3660 | 4.1240 | 0.4143 |
| 1.6942 | 0.95 | 3680 | 4.1595 | 0.4143 |
| 0.9358 | 0.96 | 3700 | 4.2914 | 0.4143 |
| 0.9632 | 0.96 | 3720 | 4.3381 | 0.4143 |
| 1.4406 | 0.97 | 3740 | 4.2782 | 0.4143 |
| 1.5333 | 0.97 | 3760 | 4.1569 | 0.4143 |
| 2.8499 | 0.98 | 3780 | 3.9997 | 0.4143 |
| 1.3767 | 0.98 | 3800 | 3.9549 | 0.4143 |
| 1.0074 | 0.99 | 3820 | 3.9189 | 0.4143 |
| 1.7482 | 0.99 | 3840 | 3.8958 | 0.4143 |
| 1.8591 | 1.0 | 3860 | 3.9007 | 0.4143 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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