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--- |
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license: apache-2.0 |
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base_model: BEE-spoke-data/smol_llama-220M-GQA |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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inference: |
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parameters: |
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max_new_tokens: 64 |
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do_sample: true |
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temperature: 0.8 |
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repetition_penalty: 1.05 |
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no_repeat_ngram_size: 4 |
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eta_cutoff: 0.0006 |
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renormalize_logits: true |
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widget: |
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- text: My name is El Microondas the Wise, and |
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example_title: El Microondas |
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- text: Kennesaw State University is a public |
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example_title: Kennesaw State University |
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- text: Bungie Studios is an American video game developer. They are most famous for |
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developing the award winning Halo series of video games. They also made Destiny. |
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The studio was founded |
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example_title: Bungie |
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- text: The Mona Lisa is a world-renowned painting created by |
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example_title: Mona Lisa |
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- text: The Harry Potter series, written by J.K. Rowling, begins with the book titled |
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example_title: Harry Potter Series |
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- text: 'Question: I have cities, but no houses. I have mountains, but no trees. I |
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have water, but no fish. What am I? |
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Answer:' |
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example_title: Riddle |
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- text: The process of photosynthesis involves the conversion of |
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example_title: Photosynthesis |
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- text: Jane went to the store to buy some groceries. She picked up apples, oranges, |
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and a loaf of bread. When she got home, she realized she forgot |
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example_title: Story Continuation |
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- text: 'Problem 2: If a train leaves Station A at 9:00 AM and travels at 60 mph, |
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and another train leaves Station B at 10:00 AM and travels at 80 mph, when will |
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they meet if the distance between the stations is 300 miles? |
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To determine' |
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example_title: Math Problem |
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- text: In the context of computer programming, an algorithm is |
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example_title: Algorithm Definition |
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pipeline_tag: text-generation |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# smol_llama-220M-GQA-fineweb-edu-10BT-mincols-vN |
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This model is a fine-tuned version of [BEE-spoke-data/smol_llama-220M-GQA](https://huggingface.co/BEE-spoke-data/smol_llama-220M-GQA) on the BEE-spoke-data/fineweb-edu-10BT-mincols dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7416 |
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- Accuracy: 0.4560 |
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- Num Input Tokens Seen: 10810818560 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 80085 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 1.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Input Tokens Seen | |
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|:-------------:|:------:|:-----:|:---------------:|:--------:|:-----------------:| |
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| 2.8567 | 0.0145 | 300 | 2.8291 | 0.4450 | 157286400 | |
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| 2.8517 | 0.0291 | 600 | 2.8153 | 0.4465 | 314572800 | |
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| 2.8224 | 0.0436 | 900 | 2.8025 | 0.4481 | 471859200 | |
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| 2.8178 | 0.0582 | 1200 | 2.7912 | 0.4495 | 629145600 | |
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| 2.8001 | 0.0727 | 1500 | 2.7832 | 0.4505 | 786432000 | |
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| 2.8045 | 0.0873 | 1800 | 2.7772 | 0.4512 | 943718400 | |
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| 2.8019 | 0.1018 | 2100 | 2.7729 | 0.4516 | 1101004800 | |
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| 2.7995 | 0.1164 | 2400 | 2.7691 | 0.4522 | 1258291200 | |
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| 2.8006 | 0.1309 | 2700 | 2.7657 | 0.4526 | 1415577600 | |
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| 2.7886 | 0.1455 | 3000 | 2.7631 | 0.4528 | 1572864000 | |
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| 2.7907 | 0.1600 | 3300 | 2.7606 | 0.4532 | 1730150400 | |
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| 2.7907 | 0.1746 | 3600 | 2.7588 | 0.4536 | 1887436800 | |
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| 2.7788 | 0.1891 | 3900 | 2.7569 | 0.4537 | 2044723200 | |
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| 2.7942 | 0.2037 | 4200 | 2.7552 | 0.4540 | 2202009600 | |
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| 2.793 | 0.2182 | 4500 | 2.7538 | 0.4543 | 2359296000 | |
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| 2.7958 | 0.2328 | 4800 | 2.7526 | 0.4544 | 2516582400 | |
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| 2.78 | 0.2473 | 5100 | 2.7515 | 0.4547 | 2673868800 | |
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| 2.7937 | 0.2619 | 5400 | 2.7506 | 0.4548 | 2831155200 | |
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| 2.7717 | 0.2764 | 5700 | 2.7498 | 0.4548 | 2988441600 | |
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| 2.7832 | 0.2910 | 6000 | 2.7490 | 0.4548 | 3145728000 | |
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| 2.768 | 0.3055 | 6300 | 2.7482 | 0.4550 | 3303014400 | |
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| 2.7653 | 0.3201 | 6600 | 2.7476 | 0.4551 | 3460300800 | |
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| 2.7843 | 0.3346 | 6900 | 2.7470 | 0.4551 | 3617587200 | |
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| 2.7765 | 0.3492 | 7200 | 2.7464 | 0.4550 | 3774873600 | |
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| 2.7778 | 0.3637 | 7500 | 2.7460 | 0.4552 | 3932160000 | |
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| 2.7655 | 0.3783 | 7800 | 2.7455 | 0.4553 | 4089446400 | |
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| 2.7943 | 0.3928 | 8100 | 2.7449 | 0.4554 | 4246732800 | |
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| 2.7715 | 0.4074 | 8400 | 2.7447 | 0.4552 | 4404019200 | |
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| 2.7828 | 0.4219 | 8700 | 2.7443 | 0.4554 | 4561305600 | |
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| 2.7883 | 0.4365 | 9000 | 2.7440 | 0.4556 | 4718592000 | |
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| 2.7627 | 0.4510 | 9300 | 2.7437 | 0.4556 | 4875878400 | |
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| 2.7841 | 0.4656 | 9600 | 2.7435 | 0.4557 | 5033164800 | |
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| 2.7734 | 0.4801 | 9900 | 2.7433 | 0.4557 | 5190451200 | |
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| 2.7829 | 0.4947 | 10200 | 2.7430 | 0.4557 | 5347737600 | |
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| 2.781 | 0.5092 | 10500 | 2.7429 | 0.4557 | 5505024000 | |
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| 2.7757 | 0.5238 | 10800 | 2.7428 | 0.4557 | 5662310400 | |
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| 2.779 | 0.5383 | 11100 | 2.7426 | 0.4559 | 5819596800 | |
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| 2.7771 | 0.5529 | 11400 | 2.7425 | 0.4559 | 5976883200 | |
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| 2.7828 | 0.5674 | 11700 | 2.7424 | 0.4560 | 6134169600 | |
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| 2.7814 | 0.5820 | 12000 | 2.7423 | 0.4558 | 6291456000 | |
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| 2.7735 | 0.5965 | 12300 | 2.7422 | 0.4559 | 6448742400 | |
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| 2.7848 | 0.6111 | 12600 | 2.7420 | 0.4559 | 6606028800 | |
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| 2.7748 | 0.6256 | 12900 | 2.7420 | 0.4559 | 6763315200 | |
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| 2.7697 | 0.6402 | 13200 | 2.7419 | 0.4560 | 6920601600 | |
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| 2.7689 | 0.6547 | 13500 | 2.7419 | 0.4560 | 7077888000 | |
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| 2.7747 | 0.6692 | 13800 | 2.7419 | 0.4559 | 7235174400 | |
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| 2.786 | 0.6838 | 14100 | 2.7418 | 0.4561 | 7392460800 | |
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| 2.7801 | 0.6983 | 14400 | 2.7417 | 0.4560 | 7549747200 | |
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| 2.7658 | 0.7129 | 14700 | 2.7417 | 0.4561 | 7707033600 | |
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| 2.7717 | 0.7274 | 15000 | 2.7417 | 0.4560 | 7864320000 | |
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| 2.7717 | 0.7420 | 15300 | 2.7417 | 0.4560 | 8021606400 | |
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| 2.777 | 0.7565 | 15600 | 2.7417 | 0.4559 | 8178892800 | |
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| 2.7793 | 0.7711 | 15900 | 2.7416 | 0.4560 | 8336179200 | |
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| 2.7718 | 0.7856 | 16200 | 2.7416 | 0.4559 | 8493465600 | |
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| 2.7757 | 0.8002 | 16500 | 2.7416 | 0.4560 | 8650752000 | |
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| 2.7763 | 0.8147 | 16800 | 2.7416 | 0.4559 | 8808038400 | |
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| 2.7581 | 0.8293 | 17100 | 2.7416 | 0.4559 | 8965324800 | |
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| 2.7719 | 0.8438 | 17400 | 2.7416 | 0.4560 | 9122611200 | |
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| 2.7609 | 0.8584 | 17700 | 2.7416 | 0.4560 | 9279897600 | |
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| 2.7753 | 0.8729 | 18000 | 2.7416 | 0.4559 | 9437184000 | |
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| 2.7674 | 0.8875 | 18300 | 2.7415 | 0.4560 | 9594470400 | |
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| 2.7601 | 0.9020 | 18600 | 2.7416 | 0.4560 | 9751756800 | |
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| 2.7823 | 0.9166 | 18900 | 2.7416 | 0.4560 | 9909043200 | |
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| 2.7767 | 0.9311 | 19200 | 2.7416 | 0.4560 | 10066329600 | |
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| 2.7759 | 0.9457 | 19500 | 2.7416 | 0.4560 | 10223616000 | |
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| 2.7722 | 0.9602 | 19800 | 2.7415 | 0.4560 | 10380902400 | |
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| 2.7764 | 0.9748 | 20100 | 2.7416 | 0.4560 | 10538188800 | |
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| 2.7724 | 0.9893 | 20400 | 2.7416 | 0.4559 | 10695475200 | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.1+cu118 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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