Farouk commited on
Commit
2e8fe49
·
1 Parent(s): 8667a6c

Training in progress, step 9200

Browse files
adapter_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:71b002acf3d17011705b0161aaa44213c47a84e70e2d6206150a00ad302e0671
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f0f0e4b8ba7f4aa55c23f9cd1c51ccfb7255418954bd2030a959a56f6da1c51b
3
  size 319977229
checkpoint-8400/adapter_model/adapter_model/README.md CHANGED
@@ -26,6 +26,17 @@ The following `bitsandbytes` quantization config was used during training:
26
  - bnb_4bit_use_double_quant: True
27
  - bnb_4bit_compute_dtype: bfloat16
28
 
 
 
 
 
 
 
 
 
 
 
 
29
  The following `bitsandbytes` quantization config was used during training:
30
  - load_in_8bit: False
31
  - load_in_4bit: True
@@ -38,6 +49,7 @@ The following `bitsandbytes` quantization config was used during training:
38
  - bnb_4bit_compute_dtype: bfloat16
39
  ### Framework versions
40
 
 
41
  - PEFT 0.4.0
42
  - PEFT 0.4.0
43
 
 
26
  - bnb_4bit_use_double_quant: True
27
  - bnb_4bit_compute_dtype: bfloat16
28
 
29
+ The following `bitsandbytes` quantization config was used during training:
30
+ - load_in_8bit: False
31
+ - load_in_4bit: True
32
+ - llm_int8_threshold: 6.0
33
+ - llm_int8_skip_modules: None
34
+ - llm_int8_enable_fp32_cpu_offload: False
35
+ - llm_int8_has_fp16_weight: False
36
+ - bnb_4bit_quant_type: nf4
37
+ - bnb_4bit_use_double_quant: True
38
+ - bnb_4bit_compute_dtype: bfloat16
39
+
40
  The following `bitsandbytes` quantization config was used during training:
41
  - load_in_8bit: False
42
  - load_in_4bit: True
 
49
  - bnb_4bit_compute_dtype: bfloat16
50
  ### Framework versions
51
 
52
+ - PEFT 0.4.0
53
  - PEFT 0.4.0
54
  - PEFT 0.4.0
55
 
checkpoint-8400/adapter_model/adapter_model/adapter_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:7ed5ee1aa4459a5bf1b8c9c01fa74b45bd644f2e745d58fba79a4b8f11d55b44
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:71b002acf3d17011705b0161aaa44213c47a84e70e2d6206150a00ad302e0671
3
  size 319977229
{checkpoint-7000 → checkpoint-9200}/README.md RENAMED
File without changes
{checkpoint-7000 → checkpoint-9200}/adapter_config.json RENAMED
File without changes
{checkpoint-7000 → checkpoint-9200}/adapter_model.bin RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:d6ab27a1c3698d35236625503bb2022e06fd51a055f8e63712c0013da65ab30e
3
  size 319977229
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:f0f0e4b8ba7f4aa55c23f9cd1c51ccfb7255418954bd2030a959a56f6da1c51b
3
  size 319977229
{checkpoint-7000 → checkpoint-9200}/added_tokens.json RENAMED
File without changes
{checkpoint-7000 → checkpoint-9200}/optimizer.pt RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:322db5b851129d70885d5c31a542e0b0e19ce11a87553e9b84fce28d1f3e682e
3
  size 1279539973
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:50b26866b0f6203c05bed841d574b2772bb2328e3c5c85e15b2ad50dbb728060
3
  size 1279539973
{checkpoint-7000 → checkpoint-9200}/rng_state.pth RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:ca936a3af4f02a38c0ab1dac6ac65ce31a5ef7e5782e30261b10ea1a9027c566
3
  size 14511
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:9de537ca44cb3663b97f57a0cddc5d06af4623908779e5c3fa42fd3f80a633c1
3
  size 14511
{checkpoint-7000 → checkpoint-9200}/scheduler.pt RENAMED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:47d966fd7801078b5a9187903dada1d3a439c6faaa2aacf8cb8a8b720458f099
3
  size 627
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8cf1be3c846f4a44286600d19f1ec9319c4fc765ad8c1c089d3918122af94a49
3
  size 627
{checkpoint-7000 → checkpoint-9200}/special_tokens_map.json RENAMED
File without changes
{checkpoint-7000 → checkpoint-9200}/tokenizer.model RENAMED
File without changes
{checkpoint-7000 → checkpoint-9200}/tokenizer_config.json RENAMED
File without changes
{checkpoint-7000 → checkpoint-9200}/trainer_state.json RENAMED
@@ -1,8 +1,8 @@
1
  {
2
- "best_metric": 0.5779068470001221,
3
- "best_model_checkpoint": "experts/expert-23/checkpoint-6600",
4
- "epoch": 1.6357051057366516,
5
- "global_step": 7000,
6
  "is_hyper_param_search": false,
7
  "is_local_process_zero": true,
8
  "is_world_process_zero": true,
@@ -6691,11 +6691,2112 @@
6691
  "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
6692
  "mmlu_loss": 1.2822566855669644,
6693
  "step": 7000
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6694
  }
6695
  ],
6696
  "max_steps": 10000,
6697
  "num_train_epochs": 3,
6698
- "total_flos": 8.620598361213174e+17,
6699
  "trial_name": null,
6700
  "trial_params": null
6701
  }
 
1
  {
2
+ "best_metric": 0.5677523612976074,
3
+ "best_model_checkpoint": "experts/expert-23/checkpoint-8400",
4
+ "epoch": 2.1497838532538847,
5
+ "global_step": 9200,
6
  "is_hyper_param_search": false,
7
  "is_local_process_zero": true,
8
  "is_world_process_zero": true,
 
6691
  "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
6692
  "mmlu_loss": 1.2822566855669644,
6693
  "step": 7000
6694
+ },
6695
+ {
6696
+ "epoch": 1.64,
6697
+ "learning_rate": 0.0002,
6698
+ "loss": 0.4717,
6699
+ "step": 7010
6700
+ },
6701
+ {
6702
+ "epoch": 1.64,
6703
+ "learning_rate": 0.0002,
6704
+ "loss": 0.5084,
6705
+ "step": 7020
6706
+ },
6707
+ {
6708
+ "epoch": 1.64,
6709
+ "learning_rate": 0.0002,
6710
+ "loss": 0.4909,
6711
+ "step": 7030
6712
+ },
6713
+ {
6714
+ "epoch": 1.65,
6715
+ "learning_rate": 0.0002,
6716
+ "loss": 0.5369,
6717
+ "step": 7040
6718
+ },
6719
+ {
6720
+ "epoch": 1.65,
6721
+ "learning_rate": 0.0002,
6722
+ "loss": 0.4972,
6723
+ "step": 7050
6724
+ },
6725
+ {
6726
+ "epoch": 1.65,
6727
+ "learning_rate": 0.0002,
6728
+ "loss": 0.5286,
6729
+ "step": 7060
6730
+ },
6731
+ {
6732
+ "epoch": 1.65,
6733
+ "learning_rate": 0.0002,
6734
+ "loss": 0.5543,
6735
+ "step": 7070
6736
+ },
6737
+ {
6738
+ "epoch": 1.65,
6739
+ "learning_rate": 0.0002,
6740
+ "loss": 0.584,
6741
+ "step": 7080
6742
+ },
6743
+ {
6744
+ "epoch": 1.66,
6745
+ "learning_rate": 0.0002,
6746
+ "loss": 0.5119,
6747
+ "step": 7090
6748
+ },
6749
+ {
6750
+ "epoch": 1.66,
6751
+ "learning_rate": 0.0002,
6752
+ "loss": 0.551,
6753
+ "step": 7100
6754
+ },
6755
+ {
6756
+ "epoch": 1.66,
6757
+ "learning_rate": 0.0002,
6758
+ "loss": 0.4711,
6759
+ "step": 7110
6760
+ },
6761
+ {
6762
+ "epoch": 1.66,
6763
+ "learning_rate": 0.0002,
6764
+ "loss": 0.5071,
6765
+ "step": 7120
6766
+ },
6767
+ {
6768
+ "epoch": 1.67,
6769
+ "learning_rate": 0.0002,
6770
+ "loss": 0.5325,
6771
+ "step": 7130
6772
+ },
6773
+ {
6774
+ "epoch": 1.67,
6775
+ "learning_rate": 0.0002,
6776
+ "loss": 0.4873,
6777
+ "step": 7140
6778
+ },
6779
+ {
6780
+ "epoch": 1.67,
6781
+ "learning_rate": 0.0002,
6782
+ "loss": 0.5411,
6783
+ "step": 7150
6784
+ },
6785
+ {
6786
+ "epoch": 1.67,
6787
+ "learning_rate": 0.0002,
6788
+ "loss": 0.5406,
6789
+ "step": 7160
6790
+ },
6791
+ {
6792
+ "epoch": 1.68,
6793
+ "learning_rate": 0.0002,
6794
+ "loss": 0.4826,
6795
+ "step": 7170
6796
+ },
6797
+ {
6798
+ "epoch": 1.68,
6799
+ "learning_rate": 0.0002,
6800
+ "loss": 0.4783,
6801
+ "step": 7180
6802
+ },
6803
+ {
6804
+ "epoch": 1.68,
6805
+ "learning_rate": 0.0002,
6806
+ "loss": 0.5819,
6807
+ "step": 7190
6808
+ },
6809
+ {
6810
+ "epoch": 1.68,
6811
+ "learning_rate": 0.0002,
6812
+ "loss": 0.4949,
6813
+ "step": 7200
6814
+ },
6815
+ {
6816
+ "epoch": 1.68,
6817
+ "eval_loss": 0.5744451284408569,
6818
+ "eval_runtime": 152.6177,
6819
+ "eval_samples_per_second": 6.552,
6820
+ "eval_steps_per_second": 3.276,
6821
+ "step": 7200
6822
+ },
6823
+ {
6824
+ "epoch": 1.68,
6825
+ "mmlu_eval_accuracy": 0.48974232604788454,
6826
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
6827
+ "mmlu_eval_accuracy_anatomy": 0.7142857142857143,
6828
+ "mmlu_eval_accuracy_astronomy": 0.4375,
6829
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
6830
+ "mmlu_eval_accuracy_clinical_knowledge": 0.6206896551724138,
6831
+ "mmlu_eval_accuracy_college_biology": 0.4375,
6832
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
6833
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
6834
+ "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
6835
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
6836
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
6837
+ "mmlu_eval_accuracy_computer_security": 0.6363636363636364,
6838
+ "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
6839
+ "mmlu_eval_accuracy_econometrics": 0.25,
6840
+ "mmlu_eval_accuracy_electrical_engineering": 0.1875,
6841
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
6842
+ "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
6843
+ "mmlu_eval_accuracy_global_facts": 0.4,
6844
+ "mmlu_eval_accuracy_high_school_biology": 0.5,
6845
+ "mmlu_eval_accuracy_high_school_chemistry": 0.36363636363636365,
6846
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
6847
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
6848
+ "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
6849
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
6850
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3953488372093023,
6851
+ "mmlu_eval_accuracy_high_school_mathematics": 0.13793103448275862,
6852
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5384615384615384,
6853
+ "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
6854
+ "mmlu_eval_accuracy_high_school_psychology": 0.8666666666666667,
6855
+ "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
6856
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
6857
+ "mmlu_eval_accuracy_high_school_world_history": 0.7307692307692307,
6858
+ "mmlu_eval_accuracy_human_aging": 0.5652173913043478,
6859
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
6860
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
6861
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
6862
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
6863
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
6864
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
6865
+ "mmlu_eval_accuracy_marketing": 0.76,
6866
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
6867
+ "mmlu_eval_accuracy_miscellaneous": 0.686046511627907,
6868
+ "mmlu_eval_accuracy_moral_disputes": 0.5263157894736842,
6869
+ "mmlu_eval_accuracy_moral_scenarios": 0.23,
6870
+ "mmlu_eval_accuracy_nutrition": 0.5454545454545454,
6871
+ "mmlu_eval_accuracy_philosophy": 0.5588235294117647,
6872
+ "mmlu_eval_accuracy_prehistory": 0.5714285714285714,
6873
+ "mmlu_eval_accuracy_professional_accounting": 0.22580645161290322,
6874
+ "mmlu_eval_accuracy_professional_law": 0.3764705882352941,
6875
+ "mmlu_eval_accuracy_professional_medicine": 0.5806451612903226,
6876
+ "mmlu_eval_accuracy_professional_psychology": 0.4492753623188406,
6877
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
6878
+ "mmlu_eval_accuracy_security_studies": 0.4444444444444444,
6879
+ "mmlu_eval_accuracy_sociology": 0.7727272727272727,
6880
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
6881
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
6882
+ "mmlu_eval_accuracy_world_religions": 0.6842105263157895,
6883
+ "mmlu_loss": 1.3121335907953526,
6884
+ "step": 7200
6885
+ },
6886
+ {
6887
+ "epoch": 1.68,
6888
+ "learning_rate": 0.0002,
6889
+ "loss": 0.508,
6890
+ "step": 7210
6891
+ },
6892
+ {
6893
+ "epoch": 1.69,
6894
+ "learning_rate": 0.0002,
6895
+ "loss": 0.5496,
6896
+ "step": 7220
6897
+ },
6898
+ {
6899
+ "epoch": 1.69,
6900
+ "learning_rate": 0.0002,
6901
+ "loss": 0.5196,
6902
+ "step": 7230
6903
+ },
6904
+ {
6905
+ "epoch": 1.69,
6906
+ "learning_rate": 0.0002,
6907
+ "loss": 0.5758,
6908
+ "step": 7240
6909
+ },
6910
+ {
6911
+ "epoch": 1.69,
6912
+ "learning_rate": 0.0002,
6913
+ "loss": 0.5694,
6914
+ "step": 7250
6915
+ },
6916
+ {
6917
+ "epoch": 1.7,
6918
+ "learning_rate": 0.0002,
6919
+ "loss": 0.4725,
6920
+ "step": 7260
6921
+ },
6922
+ {
6923
+ "epoch": 1.7,
6924
+ "learning_rate": 0.0002,
6925
+ "loss": 0.4957,
6926
+ "step": 7270
6927
+ },
6928
+ {
6929
+ "epoch": 1.7,
6930
+ "learning_rate": 0.0002,
6931
+ "loss": 0.5347,
6932
+ "step": 7280
6933
+ },
6934
+ {
6935
+ "epoch": 1.7,
6936
+ "learning_rate": 0.0002,
6937
+ "loss": 0.5483,
6938
+ "step": 7290
6939
+ },
6940
+ {
6941
+ "epoch": 1.71,
6942
+ "learning_rate": 0.0002,
6943
+ "loss": 0.5192,
6944
+ "step": 7300
6945
+ },
6946
+ {
6947
+ "epoch": 1.71,
6948
+ "learning_rate": 0.0002,
6949
+ "loss": 0.4902,
6950
+ "step": 7310
6951
+ },
6952
+ {
6953
+ "epoch": 1.71,
6954
+ "learning_rate": 0.0002,
6955
+ "loss": 0.5261,
6956
+ "step": 7320
6957
+ },
6958
+ {
6959
+ "epoch": 1.71,
6960
+ "learning_rate": 0.0002,
6961
+ "loss": 0.5323,
6962
+ "step": 7330
6963
+ },
6964
+ {
6965
+ "epoch": 1.72,
6966
+ "learning_rate": 0.0002,
6967
+ "loss": 0.5751,
6968
+ "step": 7340
6969
+ },
6970
+ {
6971
+ "epoch": 1.72,
6972
+ "learning_rate": 0.0002,
6973
+ "loss": 0.5226,
6974
+ "step": 7350
6975
+ },
6976
+ {
6977
+ "epoch": 1.72,
6978
+ "learning_rate": 0.0002,
6979
+ "loss": 0.4999,
6980
+ "step": 7360
6981
+ },
6982
+ {
6983
+ "epoch": 1.72,
6984
+ "learning_rate": 0.0002,
6985
+ "loss": 0.4997,
6986
+ "step": 7370
6987
+ },
6988
+ {
6989
+ "epoch": 1.72,
6990
+ "learning_rate": 0.0002,
6991
+ "loss": 0.521,
6992
+ "step": 7380
6993
+ },
6994
+ {
6995
+ "epoch": 1.73,
6996
+ "learning_rate": 0.0002,
6997
+ "loss": 0.4436,
6998
+ "step": 7390
6999
+ },
7000
+ {
7001
+ "epoch": 1.73,
7002
+ "learning_rate": 0.0002,
7003
+ "loss": 0.5247,
7004
+ "step": 7400
7005
+ },
7006
+ {
7007
+ "epoch": 1.73,
7008
+ "eval_loss": 0.5732148289680481,
7009
+ "eval_runtime": 152.8231,
7010
+ "eval_samples_per_second": 6.544,
7011
+ "eval_steps_per_second": 3.272,
7012
+ "step": 7400
7013
+ },
7014
+ {
7015
+ "epoch": 1.73,
7016
+ "mmlu_eval_accuracy": 0.49279197597631413,
7017
+ "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
7018
+ "mmlu_eval_accuracy_anatomy": 0.7142857142857143,
7019
+ "mmlu_eval_accuracy_astronomy": 0.4375,
7020
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
7021
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
7022
+ "mmlu_eval_accuracy_college_biology": 0.4375,
7023
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
7024
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
7025
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
7026
+ "mmlu_eval_accuracy_college_medicine": 0.5454545454545454,
7027
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
7028
+ "mmlu_eval_accuracy_computer_security": 0.45454545454545453,
7029
+ "mmlu_eval_accuracy_conceptual_physics": 0.3076923076923077,
7030
+ "mmlu_eval_accuracy_econometrics": 0.25,
7031
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
7032
+ "mmlu_eval_accuracy_elementary_mathematics": 0.3902439024390244,
7033
+ "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
7034
+ "mmlu_eval_accuracy_global_facts": 0.4,
7035
+ "mmlu_eval_accuracy_high_school_biology": 0.46875,
7036
+ "mmlu_eval_accuracy_high_school_chemistry": 0.45454545454545453,
7037
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
7038
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
7039
+ "mmlu_eval_accuracy_high_school_geography": 0.8636363636363636,
7040
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
7041
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3953488372093023,
7042
+ "mmlu_eval_accuracy_high_school_mathematics": 0.13793103448275862,
7043
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5,
7044
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
7045
+ "mmlu_eval_accuracy_high_school_psychology": 0.8666666666666667,
7046
+ "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
7047
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
7048
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
7049
+ "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
7050
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
7051
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
7052
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
7053
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
7054
+ "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
7055
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
7056
+ "mmlu_eval_accuracy_marketing": 0.76,
7057
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
7058
+ "mmlu_eval_accuracy_miscellaneous": 0.6976744186046512,
7059
+ "mmlu_eval_accuracy_moral_disputes": 0.5263157894736842,
7060
+ "mmlu_eval_accuracy_moral_scenarios": 0.24,
7061
+ "mmlu_eval_accuracy_nutrition": 0.5151515151515151,
7062
+ "mmlu_eval_accuracy_philosophy": 0.5882352941176471,
7063
+ "mmlu_eval_accuracy_prehistory": 0.5428571428571428,
7064
+ "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
7065
+ "mmlu_eval_accuracy_professional_law": 0.3588235294117647,
7066
+ "mmlu_eval_accuracy_professional_medicine": 0.6451612903225806,
7067
+ "mmlu_eval_accuracy_professional_psychology": 0.4782608695652174,
7068
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
7069
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
7070
+ "mmlu_eval_accuracy_sociology": 0.7272727272727273,
7071
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
7072
+ "mmlu_eval_accuracy_virology": 0.5,
7073
+ "mmlu_eval_accuracy_world_religions": 0.6842105263157895,
7074
+ "mmlu_loss": 1.3236380247472161,
7075
+ "step": 7400
7076
+ },
7077
+ {
7078
+ "epoch": 1.73,
7079
+ "learning_rate": 0.0002,
7080
+ "loss": 0.495,
7081
+ "step": 7410
7082
+ },
7083
+ {
7084
+ "epoch": 1.73,
7085
+ "learning_rate": 0.0002,
7086
+ "loss": 0.5057,
7087
+ "step": 7420
7088
+ },
7089
+ {
7090
+ "epoch": 1.74,
7091
+ "learning_rate": 0.0002,
7092
+ "loss": 0.5593,
7093
+ "step": 7430
7094
+ },
7095
+ {
7096
+ "epoch": 1.74,
7097
+ "learning_rate": 0.0002,
7098
+ "loss": 0.5041,
7099
+ "step": 7440
7100
+ },
7101
+ {
7102
+ "epoch": 1.74,
7103
+ "learning_rate": 0.0002,
7104
+ "loss": 0.4958,
7105
+ "step": 7450
7106
+ },
7107
+ {
7108
+ "epoch": 1.74,
7109
+ "learning_rate": 0.0002,
7110
+ "loss": 0.5365,
7111
+ "step": 7460
7112
+ },
7113
+ {
7114
+ "epoch": 1.75,
7115
+ "learning_rate": 0.0002,
7116
+ "loss": 0.4944,
7117
+ "step": 7470
7118
+ },
7119
+ {
7120
+ "epoch": 1.75,
7121
+ "learning_rate": 0.0002,
7122
+ "loss": 0.5392,
7123
+ "step": 7480
7124
+ },
7125
+ {
7126
+ "epoch": 1.75,
7127
+ "learning_rate": 0.0002,
7128
+ "loss": 0.4922,
7129
+ "step": 7490
7130
+ },
7131
+ {
7132
+ "epoch": 1.75,
7133
+ "learning_rate": 0.0002,
7134
+ "loss": 0.481,
7135
+ "step": 7500
7136
+ },
7137
+ {
7138
+ "epoch": 1.75,
7139
+ "learning_rate": 0.0002,
7140
+ "loss": 0.4678,
7141
+ "step": 7510
7142
+ },
7143
+ {
7144
+ "epoch": 1.76,
7145
+ "learning_rate": 0.0002,
7146
+ "loss": 0.5091,
7147
+ "step": 7520
7148
+ },
7149
+ {
7150
+ "epoch": 1.76,
7151
+ "learning_rate": 0.0002,
7152
+ "loss": 0.5951,
7153
+ "step": 7530
7154
+ },
7155
+ {
7156
+ "epoch": 1.76,
7157
+ "learning_rate": 0.0002,
7158
+ "loss": 0.4707,
7159
+ "step": 7540
7160
+ },
7161
+ {
7162
+ "epoch": 1.76,
7163
+ "learning_rate": 0.0002,
7164
+ "loss": 0.5048,
7165
+ "step": 7550
7166
+ },
7167
+ {
7168
+ "epoch": 1.77,
7169
+ "learning_rate": 0.0002,
7170
+ "loss": 0.5194,
7171
+ "step": 7560
7172
+ },
7173
+ {
7174
+ "epoch": 1.77,
7175
+ "learning_rate": 0.0002,
7176
+ "loss": 0.5447,
7177
+ "step": 7570
7178
+ },
7179
+ {
7180
+ "epoch": 1.77,
7181
+ "learning_rate": 0.0002,
7182
+ "loss": 0.507,
7183
+ "step": 7580
7184
+ },
7185
+ {
7186
+ "epoch": 1.77,
7187
+ "learning_rate": 0.0002,
7188
+ "loss": 0.5125,
7189
+ "step": 7590
7190
+ },
7191
+ {
7192
+ "epoch": 1.78,
7193
+ "learning_rate": 0.0002,
7194
+ "loss": 0.5342,
7195
+ "step": 7600
7196
+ },
7197
+ {
7198
+ "epoch": 1.78,
7199
+ "eval_loss": 0.5723159313201904,
7200
+ "eval_runtime": 152.8647,
7201
+ "eval_samples_per_second": 6.542,
7202
+ "eval_steps_per_second": 3.271,
7203
+ "step": 7600
7204
+ },
7205
+ {
7206
+ "epoch": 1.78,
7207
+ "mmlu_eval_accuracy": 0.49581961367784283,
7208
+ "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
7209
+ "mmlu_eval_accuracy_anatomy": 0.7857142857142857,
7210
+ "mmlu_eval_accuracy_astronomy": 0.4375,
7211
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
7212
+ "mmlu_eval_accuracy_clinical_knowledge": 0.6551724137931034,
7213
+ "mmlu_eval_accuracy_college_biology": 0.4375,
7214
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
7215
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
7216
+ "mmlu_eval_accuracy_college_mathematics": 0.18181818181818182,
7217
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
7218
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
7219
+ "mmlu_eval_accuracy_computer_security": 0.5454545454545454,
7220
+ "mmlu_eval_accuracy_conceptual_physics": 0.34615384615384615,
7221
+ "mmlu_eval_accuracy_econometrics": 0.25,
7222
+ "mmlu_eval_accuracy_electrical_engineering": 0.25,
7223
+ "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073,
7224
+ "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
7225
+ "mmlu_eval_accuracy_global_facts": 0.4,
7226
+ "mmlu_eval_accuracy_high_school_biology": 0.46875,
7227
+ "mmlu_eval_accuracy_high_school_chemistry": 0.5,
7228
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
7229
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
7230
+ "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
7231
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
7232
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4186046511627907,
7233
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
7234
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5,
7235
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
7236
+ "mmlu_eval_accuracy_high_school_psychology": 0.8666666666666667,
7237
+ "mmlu_eval_accuracy_high_school_statistics": 0.43478260869565216,
7238
+ "mmlu_eval_accuracy_high_school_us_history": 0.6818181818181818,
7239
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
7240
+ "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
7241
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
7242
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
7243
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
7244
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
7245
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
7246
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
7247
+ "mmlu_eval_accuracy_marketing": 0.84,
7248
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
7249
+ "mmlu_eval_accuracy_miscellaneous": 0.686046511627907,
7250
+ "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
7251
+ "mmlu_eval_accuracy_moral_scenarios": 0.24,
7252
+ "mmlu_eval_accuracy_nutrition": 0.5151515151515151,
7253
+ "mmlu_eval_accuracy_philosophy": 0.6176470588235294,
7254
+ "mmlu_eval_accuracy_prehistory": 0.5428571428571428,
7255
+ "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
7256
+ "mmlu_eval_accuracy_professional_law": 0.37058823529411766,
7257
+ "mmlu_eval_accuracy_professional_medicine": 0.6129032258064516,
7258
+ "mmlu_eval_accuracy_professional_psychology": 0.463768115942029,
7259
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
7260
+ "mmlu_eval_accuracy_security_studies": 0.4444444444444444,
7261
+ "mmlu_eval_accuracy_sociology": 0.8181818181818182,
7262
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
7263
+ "mmlu_eval_accuracy_virology": 0.5,
7264
+ "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
7265
+ "mmlu_loss": 1.2824829157354316,
7266
+ "step": 7600
7267
+ },
7268
+ {
7269
+ "epoch": 1.78,
7270
+ "learning_rate": 0.0002,
7271
+ "loss": 0.475,
7272
+ "step": 7610
7273
+ },
7274
+ {
7275
+ "epoch": 1.78,
7276
+ "learning_rate": 0.0002,
7277
+ "loss": 0.5073,
7278
+ "step": 7620
7279
+ },
7280
+ {
7281
+ "epoch": 1.78,
7282
+ "learning_rate": 0.0002,
7283
+ "loss": 0.5217,
7284
+ "step": 7630
7285
+ },
7286
+ {
7287
+ "epoch": 1.79,
7288
+ "learning_rate": 0.0002,
7289
+ "loss": 0.549,
7290
+ "step": 7640
7291
+ },
7292
+ {
7293
+ "epoch": 1.79,
7294
+ "learning_rate": 0.0002,
7295
+ "loss": 0.4688,
7296
+ "step": 7650
7297
+ },
7298
+ {
7299
+ "epoch": 1.79,
7300
+ "learning_rate": 0.0002,
7301
+ "loss": 0.4949,
7302
+ "step": 7660
7303
+ },
7304
+ {
7305
+ "epoch": 1.79,
7306
+ "learning_rate": 0.0002,
7307
+ "loss": 0.5198,
7308
+ "step": 7670
7309
+ },
7310
+ {
7311
+ "epoch": 1.79,
7312
+ "learning_rate": 0.0002,
7313
+ "loss": 0.508,
7314
+ "step": 7680
7315
+ },
7316
+ {
7317
+ "epoch": 1.8,
7318
+ "learning_rate": 0.0002,
7319
+ "loss": 0.5474,
7320
+ "step": 7690
7321
+ },
7322
+ {
7323
+ "epoch": 1.8,
7324
+ "learning_rate": 0.0002,
7325
+ "loss": 0.4885,
7326
+ "step": 7700
7327
+ },
7328
+ {
7329
+ "epoch": 1.8,
7330
+ "learning_rate": 0.0002,
7331
+ "loss": 0.5186,
7332
+ "step": 7710
7333
+ },
7334
+ {
7335
+ "epoch": 1.8,
7336
+ "learning_rate": 0.0002,
7337
+ "loss": 0.461,
7338
+ "step": 7720
7339
+ },
7340
+ {
7341
+ "epoch": 1.81,
7342
+ "learning_rate": 0.0002,
7343
+ "loss": 0.5265,
7344
+ "step": 7730
7345
+ },
7346
+ {
7347
+ "epoch": 1.81,
7348
+ "learning_rate": 0.0002,
7349
+ "loss": 0.5737,
7350
+ "step": 7740
7351
+ },
7352
+ {
7353
+ "epoch": 1.81,
7354
+ "learning_rate": 0.0002,
7355
+ "loss": 0.4399,
7356
+ "step": 7750
7357
+ },
7358
+ {
7359
+ "epoch": 1.81,
7360
+ "learning_rate": 0.0002,
7361
+ "loss": 0.4567,
7362
+ "step": 7760
7363
+ },
7364
+ {
7365
+ "epoch": 1.82,
7366
+ "learning_rate": 0.0002,
7367
+ "loss": 0.5372,
7368
+ "step": 7770
7369
+ },
7370
+ {
7371
+ "epoch": 1.82,
7372
+ "learning_rate": 0.0002,
7373
+ "loss": 0.4864,
7374
+ "step": 7780
7375
+ },
7376
+ {
7377
+ "epoch": 1.82,
7378
+ "learning_rate": 0.0002,
7379
+ "loss": 0.492,
7380
+ "step": 7790
7381
+ },
7382
+ {
7383
+ "epoch": 1.82,
7384
+ "learning_rate": 0.0002,
7385
+ "loss": 0.5211,
7386
+ "step": 7800
7387
+ },
7388
+ {
7389
+ "epoch": 1.82,
7390
+ "eval_loss": 0.5731128454208374,
7391
+ "eval_runtime": 152.7165,
7392
+ "eval_samples_per_second": 6.548,
7393
+ "eval_steps_per_second": 3.274,
7394
+ "step": 7800
7395
+ },
7396
+ {
7397
+ "epoch": 1.82,
7398
+ "mmlu_eval_accuracy": 0.496647897623318,
7399
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
7400
+ "mmlu_eval_accuracy_anatomy": 0.7857142857142857,
7401
+ "mmlu_eval_accuracy_astronomy": 0.5,
7402
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
7403
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5517241379310345,
7404
+ "mmlu_eval_accuracy_college_biology": 0.5625,
7405
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
7406
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
7407
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
7408
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
7409
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
7410
+ "mmlu_eval_accuracy_computer_security": 0.6363636363636364,
7411
+ "mmlu_eval_accuracy_conceptual_physics": 0.34615384615384615,
7412
+ "mmlu_eval_accuracy_econometrics": 0.25,
7413
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
7414
+ "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073,
7415
+ "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
7416
+ "mmlu_eval_accuracy_global_facts": 0.4,
7417
+ "mmlu_eval_accuracy_high_school_biology": 0.5,
7418
+ "mmlu_eval_accuracy_high_school_chemistry": 0.5,
7419
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
7420
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
7421
+ "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
7422
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
7423
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4186046511627907,
7424
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
7425
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5,
7426
+ "mmlu_eval_accuracy_high_school_physics": 0.17647058823529413,
7427
+ "mmlu_eval_accuracy_high_school_psychology": 0.8833333333333333,
7428
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
7429
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
7430
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
7431
+ "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
7432
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
7433
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
7434
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
7435
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
7436
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
7437
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
7438
+ "mmlu_eval_accuracy_marketing": 0.76,
7439
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
7440
+ "mmlu_eval_accuracy_miscellaneous": 0.627906976744186,
7441
+ "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
7442
+ "mmlu_eval_accuracy_moral_scenarios": 0.24,
7443
+ "mmlu_eval_accuracy_nutrition": 0.5151515151515151,
7444
+ "mmlu_eval_accuracy_philosophy": 0.5588235294117647,
7445
+ "mmlu_eval_accuracy_prehistory": 0.5714285714285714,
7446
+ "mmlu_eval_accuracy_professional_accounting": 0.25806451612903225,
7447
+ "mmlu_eval_accuracy_professional_law": 0.36470588235294116,
7448
+ "mmlu_eval_accuracy_professional_medicine": 0.5806451612903226,
7449
+ "mmlu_eval_accuracy_professional_psychology": 0.4782608695652174,
7450
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
7451
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
7452
+ "mmlu_eval_accuracy_sociology": 0.6818181818181818,
7453
+ "mmlu_eval_accuracy_us_foreign_policy": 0.8181818181818182,
7454
+ "mmlu_eval_accuracy_virology": 0.5,
7455
+ "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
7456
+ "mmlu_loss": 1.416621381674672,
7457
+ "step": 7800
7458
+ },
7459
+ {
7460
+ "epoch": 1.82,
7461
+ "learning_rate": 0.0002,
7462
+ "loss": 0.4728,
7463
+ "step": 7810
7464
+ },
7465
+ {
7466
+ "epoch": 1.83,
7467
+ "learning_rate": 0.0002,
7468
+ "loss": 0.4975,
7469
+ "step": 7820
7470
+ },
7471
+ {
7472
+ "epoch": 1.83,
7473
+ "learning_rate": 0.0002,
7474
+ "loss": 0.5703,
7475
+ "step": 7830
7476
+ },
7477
+ {
7478
+ "epoch": 1.83,
7479
+ "learning_rate": 0.0002,
7480
+ "loss": 0.5189,
7481
+ "step": 7840
7482
+ },
7483
+ {
7484
+ "epoch": 1.83,
7485
+ "learning_rate": 0.0002,
7486
+ "loss": 0.5736,
7487
+ "step": 7850
7488
+ },
7489
+ {
7490
+ "epoch": 1.84,
7491
+ "learning_rate": 0.0002,
7492
+ "loss": 0.5277,
7493
+ "step": 7860
7494
+ },
7495
+ {
7496
+ "epoch": 1.84,
7497
+ "learning_rate": 0.0002,
7498
+ "loss": 0.5193,
7499
+ "step": 7870
7500
+ },
7501
+ {
7502
+ "epoch": 1.84,
7503
+ "learning_rate": 0.0002,
7504
+ "loss": 0.4728,
7505
+ "step": 7880
7506
+ },
7507
+ {
7508
+ "epoch": 1.84,
7509
+ "learning_rate": 0.0002,
7510
+ "loss": 0.4855,
7511
+ "step": 7890
7512
+ },
7513
+ {
7514
+ "epoch": 1.85,
7515
+ "learning_rate": 0.0002,
7516
+ "loss": 0.4867,
7517
+ "step": 7900
7518
+ },
7519
+ {
7520
+ "epoch": 1.85,
7521
+ "learning_rate": 0.0002,
7522
+ "loss": 0.4549,
7523
+ "step": 7910
7524
+ },
7525
+ {
7526
+ "epoch": 1.85,
7527
+ "learning_rate": 0.0002,
7528
+ "loss": 0.555,
7529
+ "step": 7920
7530
+ },
7531
+ {
7532
+ "epoch": 1.85,
7533
+ "learning_rate": 0.0002,
7534
+ "loss": 0.4743,
7535
+ "step": 7930
7536
+ },
7537
+ {
7538
+ "epoch": 1.86,
7539
+ "learning_rate": 0.0002,
7540
+ "loss": 0.5278,
7541
+ "step": 7940
7542
+ },
7543
+ {
7544
+ "epoch": 1.86,
7545
+ "learning_rate": 0.0002,
7546
+ "loss": 0.4804,
7547
+ "step": 7950
7548
+ },
7549
+ {
7550
+ "epoch": 1.86,
7551
+ "learning_rate": 0.0002,
7552
+ "loss": 0.5077,
7553
+ "step": 7960
7554
+ },
7555
+ {
7556
+ "epoch": 1.86,
7557
+ "learning_rate": 0.0002,
7558
+ "loss": 0.5316,
7559
+ "step": 7970
7560
+ },
7561
+ {
7562
+ "epoch": 1.86,
7563
+ "learning_rate": 0.0002,
7564
+ "loss": 0.4947,
7565
+ "step": 7980
7566
+ },
7567
+ {
7568
+ "epoch": 1.87,
7569
+ "learning_rate": 0.0002,
7570
+ "loss": 0.5343,
7571
+ "step": 7990
7572
+ },
7573
+ {
7574
+ "epoch": 1.87,
7575
+ "learning_rate": 0.0002,
7576
+ "loss": 0.5369,
7577
+ "step": 8000
7578
+ },
7579
+ {
7580
+ "epoch": 1.87,
7581
+ "eval_loss": 0.5701168179512024,
7582
+ "eval_runtime": 152.8421,
7583
+ "eval_samples_per_second": 6.543,
7584
+ "eval_steps_per_second": 3.271,
7585
+ "step": 8000
7586
+ },
7587
+ {
7588
+ "epoch": 1.87,
7589
+ "mmlu_eval_accuracy": 0.5014867609333127,
7590
+ "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
7591
+ "mmlu_eval_accuracy_anatomy": 0.7142857142857143,
7592
+ "mmlu_eval_accuracy_astronomy": 0.5,
7593
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
7594
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5517241379310345,
7595
+ "mmlu_eval_accuracy_college_biology": 0.5625,
7596
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
7597
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
7598
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
7599
+ "mmlu_eval_accuracy_college_medicine": 0.4090909090909091,
7600
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
7601
+ "mmlu_eval_accuracy_computer_security": 0.6363636363636364,
7602
+ "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
7603
+ "mmlu_eval_accuracy_econometrics": 0.25,
7604
+ "mmlu_eval_accuracy_electrical_engineering": 0.25,
7605
+ "mmlu_eval_accuracy_elementary_mathematics": 0.3170731707317073,
7606
+ "mmlu_eval_accuracy_formal_logic": 0.35714285714285715,
7607
+ "mmlu_eval_accuracy_global_facts": 0.4,
7608
+ "mmlu_eval_accuracy_high_school_biology": 0.46875,
7609
+ "mmlu_eval_accuracy_high_school_chemistry": 0.5454545454545454,
7610
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
7611
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
7612
+ "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
7613
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
7614
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.46511627906976744,
7615
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
7616
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.5,
7617
+ "mmlu_eval_accuracy_high_school_physics": 0.17647058823529413,
7618
+ "mmlu_eval_accuracy_high_school_psychology": 0.8666666666666667,
7619
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
7620
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
7621
+ "mmlu_eval_accuracy_high_school_world_history": 0.6923076923076923,
7622
+ "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
7623
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
7624
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
7625
+ "mmlu_eval_accuracy_jurisprudence": 0.36363636363636365,
7626
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
7627
+ "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
7628
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
7629
+ "mmlu_eval_accuracy_marketing": 0.8,
7630
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
7631
+ "mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
7632
+ "mmlu_eval_accuracy_moral_disputes": 0.42105263157894735,
7633
+ "mmlu_eval_accuracy_moral_scenarios": 0.24,
7634
+ "mmlu_eval_accuracy_nutrition": 0.5757575757575758,
7635
+ "mmlu_eval_accuracy_philosophy": 0.6176470588235294,
7636
+ "mmlu_eval_accuracy_prehistory": 0.5714285714285714,
7637
+ "mmlu_eval_accuracy_professional_accounting": 0.2903225806451613,
7638
+ "mmlu_eval_accuracy_professional_law": 0.3588235294117647,
7639
+ "mmlu_eval_accuracy_professional_medicine": 0.5806451612903226,
7640
+ "mmlu_eval_accuracy_professional_psychology": 0.4782608695652174,
7641
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
7642
+ "mmlu_eval_accuracy_security_studies": 0.4444444444444444,
7643
+ "mmlu_eval_accuracy_sociology": 0.7727272727272727,
7644
+ "mmlu_eval_accuracy_us_foreign_policy": 0.8181818181818182,
7645
+ "mmlu_eval_accuracy_virology": 0.5555555555555556,
7646
+ "mmlu_eval_accuracy_world_religions": 0.6842105263157895,
7647
+ "mmlu_loss": 1.4548767866571641,
7648
+ "step": 8000
7649
+ },
7650
+ {
7651
+ "epoch": 1.87,
7652
+ "learning_rate": 0.0002,
7653
+ "loss": 0.4849,
7654
+ "step": 8010
7655
+ },
7656
+ {
7657
+ "epoch": 1.87,
7658
+ "learning_rate": 0.0002,
7659
+ "loss": 0.5057,
7660
+ "step": 8020
7661
+ },
7662
+ {
7663
+ "epoch": 1.88,
7664
+ "learning_rate": 0.0002,
7665
+ "loss": 0.5085,
7666
+ "step": 8030
7667
+ },
7668
+ {
7669
+ "epoch": 1.88,
7670
+ "learning_rate": 0.0002,
7671
+ "loss": 0.5365,
7672
+ "step": 8040
7673
+ },
7674
+ {
7675
+ "epoch": 1.88,
7676
+ "learning_rate": 0.0002,
7677
+ "loss": 0.4935,
7678
+ "step": 8050
7679
+ },
7680
+ {
7681
+ "epoch": 1.88,
7682
+ "learning_rate": 0.0002,
7683
+ "loss": 0.4998,
7684
+ "step": 8060
7685
+ },
7686
+ {
7687
+ "epoch": 1.89,
7688
+ "learning_rate": 0.0002,
7689
+ "loss": 0.5114,
7690
+ "step": 8070
7691
+ },
7692
+ {
7693
+ "epoch": 1.89,
7694
+ "learning_rate": 0.0002,
7695
+ "loss": 0.4955,
7696
+ "step": 8080
7697
+ },
7698
+ {
7699
+ "epoch": 1.89,
7700
+ "learning_rate": 0.0002,
7701
+ "loss": 0.4894,
7702
+ "step": 8090
7703
+ },
7704
+ {
7705
+ "epoch": 1.89,
7706
+ "learning_rate": 0.0002,
7707
+ "loss": 0.49,
7708
+ "step": 8100
7709
+ },
7710
+ {
7711
+ "epoch": 1.9,
7712
+ "learning_rate": 0.0002,
7713
+ "loss": 0.5173,
7714
+ "step": 8110
7715
+ },
7716
+ {
7717
+ "epoch": 1.9,
7718
+ "learning_rate": 0.0002,
7719
+ "loss": 0.5603,
7720
+ "step": 8120
7721
+ },
7722
+ {
7723
+ "epoch": 1.9,
7724
+ "learning_rate": 0.0002,
7725
+ "loss": 0.4892,
7726
+ "step": 8130
7727
+ },
7728
+ {
7729
+ "epoch": 1.9,
7730
+ "learning_rate": 0.0002,
7731
+ "loss": 0.4921,
7732
+ "step": 8140
7733
+ },
7734
+ {
7735
+ "epoch": 1.9,
7736
+ "learning_rate": 0.0002,
7737
+ "loss": 0.4974,
7738
+ "step": 8150
7739
+ },
7740
+ {
7741
+ "epoch": 1.91,
7742
+ "learning_rate": 0.0002,
7743
+ "loss": 0.5135,
7744
+ "step": 8160
7745
+ },
7746
+ {
7747
+ "epoch": 1.91,
7748
+ "learning_rate": 0.0002,
7749
+ "loss": 0.5006,
7750
+ "step": 8170
7751
+ },
7752
+ {
7753
+ "epoch": 1.91,
7754
+ "learning_rate": 0.0002,
7755
+ "loss": 0.5051,
7756
+ "step": 8180
7757
+ },
7758
+ {
7759
+ "epoch": 1.91,
7760
+ "learning_rate": 0.0002,
7761
+ "loss": 0.5242,
7762
+ "step": 8190
7763
+ },
7764
+ {
7765
+ "epoch": 1.92,
7766
+ "learning_rate": 0.0002,
7767
+ "loss": 0.5045,
7768
+ "step": 8200
7769
+ },
7770
+ {
7771
+ "epoch": 1.92,
7772
+ "eval_loss": 0.569364607334137,
7773
+ "eval_runtime": 152.8251,
7774
+ "eval_samples_per_second": 6.543,
7775
+ "eval_steps_per_second": 3.272,
7776
+ "step": 8200
7777
+ },
7778
+ {
7779
+ "epoch": 1.92,
7780
+ "mmlu_eval_accuracy": 0.4963226873720947,
7781
+ "mmlu_eval_accuracy_abstract_algebra": 0.18181818181818182,
7782
+ "mmlu_eval_accuracy_anatomy": 0.7142857142857143,
7783
+ "mmlu_eval_accuracy_astronomy": 0.5,
7784
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
7785
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
7786
+ "mmlu_eval_accuracy_college_biology": 0.375,
7787
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
7788
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
7789
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
7790
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
7791
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
7792
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
7793
+ "mmlu_eval_accuracy_conceptual_physics": 0.4230769230769231,
7794
+ "mmlu_eval_accuracy_econometrics": 0.25,
7795
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
7796
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
7797
+ "mmlu_eval_accuracy_formal_logic": 0.2857142857142857,
7798
+ "mmlu_eval_accuracy_global_facts": 0.4,
7799
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
7800
+ "mmlu_eval_accuracy_high_school_chemistry": 0.5,
7801
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
7802
+ "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
7803
+ "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
7804
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
7805
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4418604651162791,
7806
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
7807
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.4230769230769231,
7808
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
7809
+ "mmlu_eval_accuracy_high_school_psychology": 0.8666666666666667,
7810
+ "mmlu_eval_accuracy_high_school_statistics": 0.43478260869565216,
7811
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
7812
+ "mmlu_eval_accuracy_high_school_world_history": 0.7307692307692307,
7813
+ "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
7814
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
7815
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
7816
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
7817
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
7818
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
7819
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
7820
+ "mmlu_eval_accuracy_marketing": 0.8,
7821
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
7822
+ "mmlu_eval_accuracy_miscellaneous": 0.6976744186046512,
7823
+ "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
7824
+ "mmlu_eval_accuracy_moral_scenarios": 0.24,
7825
+ "mmlu_eval_accuracy_nutrition": 0.5454545454545454,
7826
+ "mmlu_eval_accuracy_philosophy": 0.6176470588235294,
7827
+ "mmlu_eval_accuracy_prehistory": 0.5428571428571428,
7828
+ "mmlu_eval_accuracy_professional_accounting": 0.16129032258064516,
7829
+ "mmlu_eval_accuracy_professional_law": 0.37058823529411766,
7830
+ "mmlu_eval_accuracy_professional_medicine": 0.6451612903225806,
7831
+ "mmlu_eval_accuracy_professional_psychology": 0.4782608695652174,
7832
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
7833
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
7834
+ "mmlu_eval_accuracy_sociology": 0.8181818181818182,
7835
+ "mmlu_eval_accuracy_us_foreign_policy": 0.8181818181818182,
7836
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
7837
+ "mmlu_eval_accuracy_world_religions": 0.7368421052631579,
7838
+ "mmlu_loss": 1.3955615495110305,
7839
+ "step": 8200
7840
+ },
7841
+ {
7842
+ "epoch": 1.92,
7843
+ "learning_rate": 0.0002,
7844
+ "loss": 0.5619,
7845
+ "step": 8210
7846
+ },
7847
+ {
7848
+ "epoch": 1.92,
7849
+ "learning_rate": 0.0002,
7850
+ "loss": 0.5232,
7851
+ "step": 8220
7852
+ },
7853
+ {
7854
+ "epoch": 1.92,
7855
+ "learning_rate": 0.0002,
7856
+ "loss": 0.4671,
7857
+ "step": 8230
7858
+ },
7859
+ {
7860
+ "epoch": 1.93,
7861
+ "learning_rate": 0.0002,
7862
+ "loss": 0.521,
7863
+ "step": 8240
7864
+ },
7865
+ {
7866
+ "epoch": 1.93,
7867
+ "learning_rate": 0.0002,
7868
+ "loss": 0.5025,
7869
+ "step": 8250
7870
+ },
7871
+ {
7872
+ "epoch": 1.93,
7873
+ "learning_rate": 0.0002,
7874
+ "loss": 0.5928,
7875
+ "step": 8260
7876
+ },
7877
+ {
7878
+ "epoch": 1.93,
7879
+ "learning_rate": 0.0002,
7880
+ "loss": 0.5085,
7881
+ "step": 8270
7882
+ },
7883
+ {
7884
+ "epoch": 1.93,
7885
+ "learning_rate": 0.0002,
7886
+ "loss": 0.5197,
7887
+ "step": 8280
7888
+ },
7889
+ {
7890
+ "epoch": 1.94,
7891
+ "learning_rate": 0.0002,
7892
+ "loss": 0.4555,
7893
+ "step": 8290
7894
+ },
7895
+ {
7896
+ "epoch": 1.94,
7897
+ "learning_rate": 0.0002,
7898
+ "loss": 0.4964,
7899
+ "step": 8300
7900
+ },
7901
+ {
7902
+ "epoch": 1.94,
7903
+ "learning_rate": 0.0002,
7904
+ "loss": 0.5154,
7905
+ "step": 8310
7906
+ },
7907
+ {
7908
+ "epoch": 1.94,
7909
+ "learning_rate": 0.0002,
7910
+ "loss": 0.5453,
7911
+ "step": 8320
7912
+ },
7913
+ {
7914
+ "epoch": 1.95,
7915
+ "learning_rate": 0.0002,
7916
+ "loss": 0.4779,
7917
+ "step": 8330
7918
+ },
7919
+ {
7920
+ "epoch": 1.95,
7921
+ "learning_rate": 0.0002,
7922
+ "loss": 0.544,
7923
+ "step": 8340
7924
+ },
7925
+ {
7926
+ "epoch": 1.95,
7927
+ "learning_rate": 0.0002,
7928
+ "loss": 0.5561,
7929
+ "step": 8350
7930
+ },
7931
+ {
7932
+ "epoch": 1.95,
7933
+ "learning_rate": 0.0002,
7934
+ "loss": 0.4826,
7935
+ "step": 8360
7936
+ },
7937
+ {
7938
+ "epoch": 1.96,
7939
+ "learning_rate": 0.0002,
7940
+ "loss": 0.5273,
7941
+ "step": 8370
7942
+ },
7943
+ {
7944
+ "epoch": 1.96,
7945
+ "learning_rate": 0.0002,
7946
+ "loss": 0.5349,
7947
+ "step": 8380
7948
+ },
7949
+ {
7950
+ "epoch": 1.96,
7951
+ "learning_rate": 0.0002,
7952
+ "loss": 0.4882,
7953
+ "step": 8390
7954
+ },
7955
+ {
7956
+ "epoch": 1.96,
7957
+ "learning_rate": 0.0002,
7958
+ "loss": 0.4903,
7959
+ "step": 8400
7960
+ },
7961
+ {
7962
+ "epoch": 1.96,
7963
+ "eval_loss": 0.5677523612976074,
7964
+ "eval_runtime": 152.839,
7965
+ "eval_samples_per_second": 6.543,
7966
+ "eval_steps_per_second": 3.271,
7967
+ "step": 8400
7968
+ },
7969
+ {
7970
+ "epoch": 1.96,
7971
+ "mmlu_eval_accuracy": 0.5060261139794974,
7972
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
7973
+ "mmlu_eval_accuracy_anatomy": 0.7857142857142857,
7974
+ "mmlu_eval_accuracy_astronomy": 0.5,
7975
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
7976
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5517241379310345,
7977
+ "mmlu_eval_accuracy_college_biology": 0.5625,
7978
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
7979
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
7980
+ "mmlu_eval_accuracy_college_mathematics": 0.36363636363636365,
7981
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
7982
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
7983
+ "mmlu_eval_accuracy_computer_security": 0.5454545454545454,
7984
+ "mmlu_eval_accuracy_conceptual_physics": 0.38461538461538464,
7985
+ "mmlu_eval_accuracy_econometrics": 0.25,
7986
+ "mmlu_eval_accuracy_electrical_engineering": 0.25,
7987
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
7988
+ "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
7989
+ "mmlu_eval_accuracy_global_facts": 0.4,
7990
+ "mmlu_eval_accuracy_high_school_biology": 0.46875,
7991
+ "mmlu_eval_accuracy_high_school_chemistry": 0.5,
7992
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
7993
+ "mmlu_eval_accuracy_high_school_european_history": 0.6111111111111112,
7994
+ "mmlu_eval_accuracy_high_school_geography": 0.8181818181818182,
7995
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
7996
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.37209302325581395,
7997
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
7998
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.46153846153846156,
7999
+ "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
8000
+ "mmlu_eval_accuracy_high_school_psychology": 0.85,
8001
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
8002
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
8003
+ "mmlu_eval_accuracy_high_school_world_history": 0.6923076923076923,
8004
+ "mmlu_eval_accuracy_human_aging": 0.6956521739130435,
8005
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
8006
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
8007
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
8008
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
8009
+ "mmlu_eval_accuracy_machine_learning": 0.36363636363636365,
8010
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
8011
+ "mmlu_eval_accuracy_marketing": 0.8,
8012
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
8013
+ "mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
8014
+ "mmlu_eval_accuracy_moral_disputes": 0.39473684210526316,
8015
+ "mmlu_eval_accuracy_moral_scenarios": 0.25,
8016
+ "mmlu_eval_accuracy_nutrition": 0.48484848484848486,
8017
+ "mmlu_eval_accuracy_philosophy": 0.5588235294117647,
8018
+ "mmlu_eval_accuracy_prehistory": 0.5714285714285714,
8019
+ "mmlu_eval_accuracy_professional_accounting": 0.16129032258064516,
8020
+ "mmlu_eval_accuracy_professional_law": 0.37058823529411766,
8021
+ "mmlu_eval_accuracy_professional_medicine": 0.5806451612903226,
8022
+ "mmlu_eval_accuracy_professional_psychology": 0.5072463768115942,
8023
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
8024
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
8025
+ "mmlu_eval_accuracy_sociology": 0.7727272727272727,
8026
+ "mmlu_eval_accuracy_us_foreign_policy": 0.8181818181818182,
8027
+ "mmlu_eval_accuracy_virology": 0.5,
8028
+ "mmlu_eval_accuracy_world_religions": 0.6842105263157895,
8029
+ "mmlu_loss": 1.3605959965572656,
8030
+ "step": 8400
8031
+ },
8032
+ {
8033
+ "epoch": 1.97,
8034
+ "learning_rate": 0.0002,
8035
+ "loss": 0.5089,
8036
+ "step": 8410
8037
+ },
8038
+ {
8039
+ "epoch": 1.97,
8040
+ "learning_rate": 0.0002,
8041
+ "loss": 0.5067,
8042
+ "step": 8420
8043
+ },
8044
+ {
8045
+ "epoch": 1.97,
8046
+ "learning_rate": 0.0002,
8047
+ "loss": 0.4525,
8048
+ "step": 8430
8049
+ },
8050
+ {
8051
+ "epoch": 1.97,
8052
+ "learning_rate": 0.0002,
8053
+ "loss": 0.5447,
8054
+ "step": 8440
8055
+ },
8056
+ {
8057
+ "epoch": 1.97,
8058
+ "learning_rate": 0.0002,
8059
+ "loss": 0.5106,
8060
+ "step": 8450
8061
+ },
8062
+ {
8063
+ "epoch": 1.98,
8064
+ "learning_rate": 0.0002,
8065
+ "loss": 0.4842,
8066
+ "step": 8460
8067
+ },
8068
+ {
8069
+ "epoch": 1.98,
8070
+ "learning_rate": 0.0002,
8071
+ "loss": 0.4446,
8072
+ "step": 8470
8073
+ },
8074
+ {
8075
+ "epoch": 1.98,
8076
+ "learning_rate": 0.0002,
8077
+ "loss": 0.4708,
8078
+ "step": 8480
8079
+ },
8080
+ {
8081
+ "epoch": 1.98,
8082
+ "learning_rate": 0.0002,
8083
+ "loss": 0.5378,
8084
+ "step": 8490
8085
+ },
8086
+ {
8087
+ "epoch": 1.99,
8088
+ "learning_rate": 0.0002,
8089
+ "loss": 0.5073,
8090
+ "step": 8500
8091
+ },
8092
+ {
8093
+ "epoch": 1.99,
8094
+ "learning_rate": 0.0002,
8095
+ "loss": 0.4609,
8096
+ "step": 8510
8097
+ },
8098
+ {
8099
+ "epoch": 1.99,
8100
+ "learning_rate": 0.0002,
8101
+ "loss": 0.4446,
8102
+ "step": 8520
8103
+ },
8104
+ {
8105
+ "epoch": 1.99,
8106
+ "learning_rate": 0.0002,
8107
+ "loss": 0.4677,
8108
+ "step": 8530
8109
+ },
8110
+ {
8111
+ "epoch": 2.0,
8112
+ "learning_rate": 0.0002,
8113
+ "loss": 0.5153,
8114
+ "step": 8540
8115
+ },
8116
+ {
8117
+ "epoch": 2.0,
8118
+ "learning_rate": 0.0002,
8119
+ "loss": 0.5209,
8120
+ "step": 8550
8121
+ },
8122
+ {
8123
+ "epoch": 2.0,
8124
+ "learning_rate": 0.0002,
8125
+ "loss": 0.502,
8126
+ "step": 8560
8127
+ },
8128
+ {
8129
+ "epoch": 2.0,
8130
+ "learning_rate": 0.0002,
8131
+ "loss": 0.3987,
8132
+ "step": 8570
8133
+ },
8134
+ {
8135
+ "epoch": 2.0,
8136
+ "learning_rate": 0.0002,
8137
+ "loss": 0.4131,
8138
+ "step": 8580
8139
+ },
8140
+ {
8141
+ "epoch": 2.01,
8142
+ "learning_rate": 0.0002,
8143
+ "loss": 0.437,
8144
+ "step": 8590
8145
+ },
8146
+ {
8147
+ "epoch": 2.01,
8148
+ "learning_rate": 0.0002,
8149
+ "loss": 0.3685,
8150
+ "step": 8600
8151
+ },
8152
+ {
8153
+ "epoch": 2.01,
8154
+ "eval_loss": 0.5845896005630493,
8155
+ "eval_runtime": 152.7661,
8156
+ "eval_samples_per_second": 6.546,
8157
+ "eval_steps_per_second": 3.273,
8158
+ "step": 8600
8159
+ },
8160
+ {
8161
+ "epoch": 2.01,
8162
+ "mmlu_eval_accuracy": 0.48527573542890506,
8163
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
8164
+ "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
8165
+ "mmlu_eval_accuracy_astronomy": 0.5,
8166
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
8167
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5172413793103449,
8168
+ "mmlu_eval_accuracy_college_biology": 0.3125,
8169
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
8170
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
8171
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
8172
+ "mmlu_eval_accuracy_college_medicine": 0.5454545454545454,
8173
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
8174
+ "mmlu_eval_accuracy_computer_security": 0.36363636363636365,
8175
+ "mmlu_eval_accuracy_conceptual_physics": 0.34615384615384615,
8176
+ "mmlu_eval_accuracy_econometrics": 0.25,
8177
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
8178
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
8179
+ "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
8180
+ "mmlu_eval_accuracy_global_facts": 0.4,
8181
+ "mmlu_eval_accuracy_high_school_biology": 0.4375,
8182
+ "mmlu_eval_accuracy_high_school_chemistry": 0.5454545454545454,
8183
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
8184
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
8185
+ "mmlu_eval_accuracy_high_school_geography": 0.8181818181818182,
8186
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
8187
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3953488372093023,
8188
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
8189
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.38461538461538464,
8190
+ "mmlu_eval_accuracy_high_school_physics": 0.23529411764705882,
8191
+ "mmlu_eval_accuracy_high_school_psychology": 0.85,
8192
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
8193
+ "mmlu_eval_accuracy_high_school_us_history": 0.6818181818181818,
8194
+ "mmlu_eval_accuracy_high_school_world_history": 0.6923076923076923,
8195
+ "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
8196
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
8197
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
8198
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
8199
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
8200
+ "mmlu_eval_accuracy_machine_learning": 0.2727272727272727,
8201
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
8202
+ "mmlu_eval_accuracy_marketing": 0.76,
8203
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
8204
+ "mmlu_eval_accuracy_miscellaneous": 0.6744186046511628,
8205
+ "mmlu_eval_accuracy_moral_disputes": 0.39473684210526316,
8206
+ "mmlu_eval_accuracy_moral_scenarios": 0.25,
8207
+ "mmlu_eval_accuracy_nutrition": 0.45454545454545453,
8208
+ "mmlu_eval_accuracy_philosophy": 0.5294117647058824,
8209
+ "mmlu_eval_accuracy_prehistory": 0.5428571428571428,
8210
+ "mmlu_eval_accuracy_professional_accounting": 0.16129032258064516,
8211
+ "mmlu_eval_accuracy_professional_law": 0.3764705882352941,
8212
+ "mmlu_eval_accuracy_professional_medicine": 0.5806451612903226,
8213
+ "mmlu_eval_accuracy_professional_psychology": 0.463768115942029,
8214
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
8215
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
8216
+ "mmlu_eval_accuracy_sociology": 0.7272727272727273,
8217
+ "mmlu_eval_accuracy_us_foreign_policy": 0.8181818181818182,
8218
+ "mmlu_eval_accuracy_virology": 0.5,
8219
+ "mmlu_eval_accuracy_world_religions": 0.631578947368421,
8220
+ "mmlu_loss": 1.3346116830723715,
8221
+ "step": 8600
8222
+ },
8223
+ {
8224
+ "epoch": 2.01,
8225
+ "learning_rate": 0.0002,
8226
+ "loss": 0.3693,
8227
+ "step": 8610
8228
+ },
8229
+ {
8230
+ "epoch": 2.01,
8231
+ "learning_rate": 0.0002,
8232
+ "loss": 0.3933,
8233
+ "step": 8620
8234
+ },
8235
+ {
8236
+ "epoch": 2.02,
8237
+ "learning_rate": 0.0002,
8238
+ "loss": 0.4046,
8239
+ "step": 8630
8240
+ },
8241
+ {
8242
+ "epoch": 2.02,
8243
+ "learning_rate": 0.0002,
8244
+ "loss": 0.4115,
8245
+ "step": 8640
8246
+ },
8247
+ {
8248
+ "epoch": 2.02,
8249
+ "learning_rate": 0.0002,
8250
+ "loss": 0.402,
8251
+ "step": 8650
8252
+ },
8253
+ {
8254
+ "epoch": 2.02,
8255
+ "learning_rate": 0.0002,
8256
+ "loss": 0.3827,
8257
+ "step": 8660
8258
+ },
8259
+ {
8260
+ "epoch": 2.03,
8261
+ "learning_rate": 0.0002,
8262
+ "loss": 0.4902,
8263
+ "step": 8670
8264
+ },
8265
+ {
8266
+ "epoch": 2.03,
8267
+ "learning_rate": 0.0002,
8268
+ "loss": 0.3734,
8269
+ "step": 8680
8270
+ },
8271
+ {
8272
+ "epoch": 2.03,
8273
+ "learning_rate": 0.0002,
8274
+ "loss": 0.3907,
8275
+ "step": 8690
8276
+ },
8277
+ {
8278
+ "epoch": 2.03,
8279
+ "learning_rate": 0.0002,
8280
+ "loss": 0.3763,
8281
+ "step": 8700
8282
+ },
8283
+ {
8284
+ "epoch": 2.04,
8285
+ "learning_rate": 0.0002,
8286
+ "loss": 0.3912,
8287
+ "step": 8710
8288
+ },
8289
+ {
8290
+ "epoch": 2.04,
8291
+ "learning_rate": 0.0002,
8292
+ "loss": 0.3722,
8293
+ "step": 8720
8294
+ },
8295
+ {
8296
+ "epoch": 2.04,
8297
+ "learning_rate": 0.0002,
8298
+ "loss": 0.4791,
8299
+ "step": 8730
8300
+ },
8301
+ {
8302
+ "epoch": 2.04,
8303
+ "learning_rate": 0.0002,
8304
+ "loss": 0.3953,
8305
+ "step": 8740
8306
+ },
8307
+ {
8308
+ "epoch": 2.04,
8309
+ "learning_rate": 0.0002,
8310
+ "loss": 0.4447,
8311
+ "step": 8750
8312
+ },
8313
+ {
8314
+ "epoch": 2.05,
8315
+ "learning_rate": 0.0002,
8316
+ "loss": 0.3898,
8317
+ "step": 8760
8318
+ },
8319
+ {
8320
+ "epoch": 2.05,
8321
+ "learning_rate": 0.0002,
8322
+ "loss": 0.4003,
8323
+ "step": 8770
8324
+ },
8325
+ {
8326
+ "epoch": 2.05,
8327
+ "learning_rate": 0.0002,
8328
+ "loss": 0.3652,
8329
+ "step": 8780
8330
+ },
8331
+ {
8332
+ "epoch": 2.05,
8333
+ "learning_rate": 0.0002,
8334
+ "loss": 0.402,
8335
+ "step": 8790
8336
+ },
8337
+ {
8338
+ "epoch": 2.06,
8339
+ "learning_rate": 0.0002,
8340
+ "loss": 0.4506,
8341
+ "step": 8800
8342
+ },
8343
+ {
8344
+ "epoch": 2.06,
8345
+ "eval_loss": 0.5888623595237732,
8346
+ "eval_runtime": 152.7831,
8347
+ "eval_samples_per_second": 6.545,
8348
+ "eval_steps_per_second": 3.273,
8349
+ "step": 8800
8350
+ },
8351
+ {
8352
+ "epoch": 2.06,
8353
+ "mmlu_eval_accuracy": 0.4956840418446969,
8354
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
8355
+ "mmlu_eval_accuracy_anatomy": 0.7142857142857143,
8356
+ "mmlu_eval_accuracy_astronomy": 0.5,
8357
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
8358
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5172413793103449,
8359
+ "mmlu_eval_accuracy_college_biology": 0.375,
8360
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
8361
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
8362
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
8363
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
8364
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
8365
+ "mmlu_eval_accuracy_computer_security": 0.45454545454545453,
8366
+ "mmlu_eval_accuracy_conceptual_physics": 0.3076923076923077,
8367
+ "mmlu_eval_accuracy_econometrics": 0.25,
8368
+ "mmlu_eval_accuracy_electrical_engineering": 0.25,
8369
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
8370
+ "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
8371
+ "mmlu_eval_accuracy_global_facts": 0.5,
8372
+ "mmlu_eval_accuracy_high_school_biology": 0.4375,
8373
+ "mmlu_eval_accuracy_high_school_chemistry": 0.5,
8374
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
8375
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
8376
+ "mmlu_eval_accuracy_high_school_geography": 0.8181818181818182,
8377
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6666666666666666,
8378
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.4186046511627907,
8379
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
8380
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.38461538461538464,
8381
+ "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
8382
+ "mmlu_eval_accuracy_high_school_psychology": 0.85,
8383
+ "mmlu_eval_accuracy_high_school_statistics": 0.34782608695652173,
8384
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
8385
+ "mmlu_eval_accuracy_high_school_world_history": 0.6538461538461539,
8386
+ "mmlu_eval_accuracy_human_aging": 0.6086956521739131,
8387
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
8388
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
8389
+ "mmlu_eval_accuracy_jurisprudence": 0.5454545454545454,
8390
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
8391
+ "mmlu_eval_accuracy_machine_learning": 0.36363636363636365,
8392
+ "mmlu_eval_accuracy_management": 0.6363636363636364,
8393
+ "mmlu_eval_accuracy_marketing": 0.76,
8394
+ "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
8395
+ "mmlu_eval_accuracy_miscellaneous": 0.7093023255813954,
8396
+ "mmlu_eval_accuracy_moral_disputes": 0.5,
8397
+ "mmlu_eval_accuracy_moral_scenarios": 0.23,
8398
+ "mmlu_eval_accuracy_nutrition": 0.5151515151515151,
8399
+ "mmlu_eval_accuracy_philosophy": 0.5588235294117647,
8400
+ "mmlu_eval_accuracy_prehistory": 0.5714285714285714,
8401
+ "mmlu_eval_accuracy_professional_accounting": 0.16129032258064516,
8402
+ "mmlu_eval_accuracy_professional_law": 0.3588235294117647,
8403
+ "mmlu_eval_accuracy_professional_medicine": 0.6129032258064516,
8404
+ "mmlu_eval_accuracy_professional_psychology": 0.4492753623188406,
8405
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
8406
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
8407
+ "mmlu_eval_accuracy_sociology": 0.8181818181818182,
8408
+ "mmlu_eval_accuracy_us_foreign_policy": 0.8181818181818182,
8409
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
8410
+ "mmlu_eval_accuracy_world_religions": 0.631578947368421,
8411
+ "mmlu_loss": 1.310942172323288,
8412
+ "step": 8800
8413
+ },
8414
+ {
8415
+ "epoch": 2.06,
8416
+ "learning_rate": 0.0002,
8417
+ "loss": 0.3585,
8418
+ "step": 8810
8419
+ },
8420
+ {
8421
+ "epoch": 2.06,
8422
+ "learning_rate": 0.0002,
8423
+ "loss": 0.4333,
8424
+ "step": 8820
8425
+ },
8426
+ {
8427
+ "epoch": 2.06,
8428
+ "learning_rate": 0.0002,
8429
+ "loss": 0.4002,
8430
+ "step": 8830
8431
+ },
8432
+ {
8433
+ "epoch": 2.07,
8434
+ "learning_rate": 0.0002,
8435
+ "loss": 0.3622,
8436
+ "step": 8840
8437
+ },
8438
+ {
8439
+ "epoch": 2.07,
8440
+ "learning_rate": 0.0002,
8441
+ "loss": 0.393,
8442
+ "step": 8850
8443
+ },
8444
+ {
8445
+ "epoch": 2.07,
8446
+ "learning_rate": 0.0002,
8447
+ "loss": 0.451,
8448
+ "step": 8860
8449
+ },
8450
+ {
8451
+ "epoch": 2.07,
8452
+ "learning_rate": 0.0002,
8453
+ "loss": 0.3497,
8454
+ "step": 8870
8455
+ },
8456
+ {
8457
+ "epoch": 2.08,
8458
+ "learning_rate": 0.0002,
8459
+ "loss": 0.4046,
8460
+ "step": 8880
8461
+ },
8462
+ {
8463
+ "epoch": 2.08,
8464
+ "learning_rate": 0.0002,
8465
+ "loss": 0.3804,
8466
+ "step": 8890
8467
+ },
8468
+ {
8469
+ "epoch": 2.08,
8470
+ "learning_rate": 0.0002,
8471
+ "loss": 0.4521,
8472
+ "step": 8900
8473
+ },
8474
+ {
8475
+ "epoch": 2.08,
8476
+ "learning_rate": 0.0002,
8477
+ "loss": 0.463,
8478
+ "step": 8910
8479
+ },
8480
+ {
8481
+ "epoch": 2.08,
8482
+ "learning_rate": 0.0002,
8483
+ "loss": 0.4373,
8484
+ "step": 8920
8485
+ },
8486
+ {
8487
+ "epoch": 2.09,
8488
+ "learning_rate": 0.0002,
8489
+ "loss": 0.3876,
8490
+ "step": 8930
8491
+ },
8492
+ {
8493
+ "epoch": 2.09,
8494
+ "learning_rate": 0.0002,
8495
+ "loss": 0.4704,
8496
+ "step": 8940
8497
+ },
8498
+ {
8499
+ "epoch": 2.09,
8500
+ "learning_rate": 0.0002,
8501
+ "loss": 0.4194,
8502
+ "step": 8950
8503
+ },
8504
+ {
8505
+ "epoch": 2.09,
8506
+ "learning_rate": 0.0002,
8507
+ "loss": 0.411,
8508
+ "step": 8960
8509
+ },
8510
+ {
8511
+ "epoch": 2.1,
8512
+ "learning_rate": 0.0002,
8513
+ "loss": 0.3966,
8514
+ "step": 8970
8515
+ },
8516
+ {
8517
+ "epoch": 2.1,
8518
+ "learning_rate": 0.0002,
8519
+ "loss": 0.4656,
8520
+ "step": 8980
8521
+ },
8522
+ {
8523
+ "epoch": 2.1,
8524
+ "learning_rate": 0.0002,
8525
+ "loss": 0.4144,
8526
+ "step": 8990
8527
+ },
8528
+ {
8529
+ "epoch": 2.1,
8530
+ "learning_rate": 0.0002,
8531
+ "loss": 0.3937,
8532
+ "step": 9000
8533
+ },
8534
+ {
8535
+ "epoch": 2.1,
8536
+ "eval_loss": 0.5891299247741699,
8537
+ "eval_runtime": 152.6008,
8538
+ "eval_samples_per_second": 6.553,
8539
+ "eval_steps_per_second": 3.277,
8540
+ "step": 9000
8541
+ },
8542
+ {
8543
+ "epoch": 2.1,
8544
+ "mmlu_eval_accuracy": 0.48603152016027296,
8545
+ "mmlu_eval_accuracy_abstract_algebra": 0.36363636363636365,
8546
+ "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
8547
+ "mmlu_eval_accuracy_astronomy": 0.5,
8548
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
8549
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
8550
+ "mmlu_eval_accuracy_college_biology": 0.5,
8551
+ "mmlu_eval_accuracy_college_chemistry": 0.25,
8552
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
8553
+ "mmlu_eval_accuracy_college_mathematics": 0.36363636363636365,
8554
+ "mmlu_eval_accuracy_college_medicine": 0.45454545454545453,
8555
+ "mmlu_eval_accuracy_college_physics": 0.2727272727272727,
8556
+ "mmlu_eval_accuracy_computer_security": 0.2727272727272727,
8557
+ "mmlu_eval_accuracy_conceptual_physics": 0.3076923076923077,
8558
+ "mmlu_eval_accuracy_econometrics": 0.25,
8559
+ "mmlu_eval_accuracy_electrical_engineering": 0.375,
8560
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
8561
+ "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
8562
+ "mmlu_eval_accuracy_global_facts": 0.4,
8563
+ "mmlu_eval_accuracy_high_school_biology": 0.40625,
8564
+ "mmlu_eval_accuracy_high_school_chemistry": 0.45454545454545453,
8565
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
8566
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
8567
+ "mmlu_eval_accuracy_high_school_geography": 0.8181818181818182,
8568
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.6190476190476191,
8569
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.37209302325581395,
8570
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
8571
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.34615384615384615,
8572
+ "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
8573
+ "mmlu_eval_accuracy_high_school_psychology": 0.85,
8574
+ "mmlu_eval_accuracy_high_school_statistics": 0.391304347826087,
8575
+ "mmlu_eval_accuracy_high_school_us_history": 0.6363636363636364,
8576
+ "mmlu_eval_accuracy_high_school_world_history": 0.6923076923076923,
8577
+ "mmlu_eval_accuracy_human_aging": 0.6086956521739131,
8578
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
8579
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
8580
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
8581
+ "mmlu_eval_accuracy_logical_fallacies": 0.6666666666666666,
8582
+ "mmlu_eval_accuracy_machine_learning": 0.18181818181818182,
8583
+ "mmlu_eval_accuracy_management": 0.7272727272727273,
8584
+ "mmlu_eval_accuracy_marketing": 0.68,
8585
+ "mmlu_eval_accuracy_medical_genetics": 0.8181818181818182,
8586
+ "mmlu_eval_accuracy_miscellaneous": 0.6976744186046512,
8587
+ "mmlu_eval_accuracy_moral_disputes": 0.47368421052631576,
8588
+ "mmlu_eval_accuracy_moral_scenarios": 0.22,
8589
+ "mmlu_eval_accuracy_nutrition": 0.45454545454545453,
8590
+ "mmlu_eval_accuracy_philosophy": 0.5882352941176471,
8591
+ "mmlu_eval_accuracy_prehistory": 0.5428571428571428,
8592
+ "mmlu_eval_accuracy_professional_accounting": 0.12903225806451613,
8593
+ "mmlu_eval_accuracy_professional_law": 0.3588235294117647,
8594
+ "mmlu_eval_accuracy_professional_medicine": 0.6129032258064516,
8595
+ "mmlu_eval_accuracy_professional_psychology": 0.463768115942029,
8596
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
8597
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
8598
+ "mmlu_eval_accuracy_sociology": 0.7272727272727273,
8599
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
8600
+ "mmlu_eval_accuracy_virology": 0.5,
8601
+ "mmlu_eval_accuracy_world_religions": 0.631578947368421,
8602
+ "mmlu_loss": 1.2810701004402134,
8603
+ "step": 9000
8604
+ },
8605
+ {
8606
+ "epoch": 2.11,
8607
+ "learning_rate": 0.0002,
8608
+ "loss": 0.4501,
8609
+ "step": 9010
8610
+ },
8611
+ {
8612
+ "epoch": 2.11,
8613
+ "learning_rate": 0.0002,
8614
+ "loss": 0.392,
8615
+ "step": 9020
8616
+ },
8617
+ {
8618
+ "epoch": 2.11,
8619
+ "learning_rate": 0.0002,
8620
+ "loss": 0.4056,
8621
+ "step": 9030
8622
+ },
8623
+ {
8624
+ "epoch": 2.11,
8625
+ "learning_rate": 0.0002,
8626
+ "loss": 0.441,
8627
+ "step": 9040
8628
+ },
8629
+ {
8630
+ "epoch": 2.11,
8631
+ "learning_rate": 0.0002,
8632
+ "loss": 0.4503,
8633
+ "step": 9050
8634
+ },
8635
+ {
8636
+ "epoch": 2.12,
8637
+ "learning_rate": 0.0002,
8638
+ "loss": 0.4112,
8639
+ "step": 9060
8640
+ },
8641
+ {
8642
+ "epoch": 2.12,
8643
+ "learning_rate": 0.0002,
8644
+ "loss": 0.402,
8645
+ "step": 9070
8646
+ },
8647
+ {
8648
+ "epoch": 2.12,
8649
+ "learning_rate": 0.0002,
8650
+ "loss": 0.3698,
8651
+ "step": 9080
8652
+ },
8653
+ {
8654
+ "epoch": 2.12,
8655
+ "learning_rate": 0.0002,
8656
+ "loss": 0.4275,
8657
+ "step": 9090
8658
+ },
8659
+ {
8660
+ "epoch": 2.13,
8661
+ "learning_rate": 0.0002,
8662
+ "loss": 0.4988,
8663
+ "step": 9100
8664
+ },
8665
+ {
8666
+ "epoch": 2.13,
8667
+ "learning_rate": 0.0002,
8668
+ "loss": 0.4009,
8669
+ "step": 9110
8670
+ },
8671
+ {
8672
+ "epoch": 2.13,
8673
+ "learning_rate": 0.0002,
8674
+ "loss": 0.3756,
8675
+ "step": 9120
8676
+ },
8677
+ {
8678
+ "epoch": 2.13,
8679
+ "learning_rate": 0.0002,
8680
+ "loss": 0.4069,
8681
+ "step": 9130
8682
+ },
8683
+ {
8684
+ "epoch": 2.14,
8685
+ "learning_rate": 0.0002,
8686
+ "loss": 0.4099,
8687
+ "step": 9140
8688
+ },
8689
+ {
8690
+ "epoch": 2.14,
8691
+ "learning_rate": 0.0002,
8692
+ "loss": 0.4582,
8693
+ "step": 9150
8694
+ },
8695
+ {
8696
+ "epoch": 2.14,
8697
+ "learning_rate": 0.0002,
8698
+ "loss": 0.3789,
8699
+ "step": 9160
8700
+ },
8701
+ {
8702
+ "epoch": 2.14,
8703
+ "learning_rate": 0.0002,
8704
+ "loss": 0.422,
8705
+ "step": 9170
8706
+ },
8707
+ {
8708
+ "epoch": 2.15,
8709
+ "learning_rate": 0.0002,
8710
+ "loss": 0.4137,
8711
+ "step": 9180
8712
+ },
8713
+ {
8714
+ "epoch": 2.15,
8715
+ "learning_rate": 0.0002,
8716
+ "loss": 0.4124,
8717
+ "step": 9190
8718
+ },
8719
+ {
8720
+ "epoch": 2.15,
8721
+ "learning_rate": 0.0002,
8722
+ "loss": 0.4122,
8723
+ "step": 9200
8724
+ },
8725
+ {
8726
+ "epoch": 2.15,
8727
+ "eval_loss": 0.592425525188446,
8728
+ "eval_runtime": 152.5674,
8729
+ "eval_samples_per_second": 6.554,
8730
+ "eval_steps_per_second": 3.277,
8731
+ "step": 9200
8732
+ },
8733
+ {
8734
+ "epoch": 2.15,
8735
+ "mmlu_eval_accuracy": 0.47734880433784366,
8736
+ "mmlu_eval_accuracy_abstract_algebra": 0.2727272727272727,
8737
+ "mmlu_eval_accuracy_anatomy": 0.6428571428571429,
8738
+ "mmlu_eval_accuracy_astronomy": 0.5,
8739
+ "mmlu_eval_accuracy_business_ethics": 0.45454545454545453,
8740
+ "mmlu_eval_accuracy_clinical_knowledge": 0.5862068965517241,
8741
+ "mmlu_eval_accuracy_college_biology": 0.375,
8742
+ "mmlu_eval_accuracy_college_chemistry": 0.125,
8743
+ "mmlu_eval_accuracy_college_computer_science": 0.36363636363636365,
8744
+ "mmlu_eval_accuracy_college_mathematics": 0.2727272727272727,
8745
+ "mmlu_eval_accuracy_college_medicine": 0.5,
8746
+ "mmlu_eval_accuracy_college_physics": 0.36363636363636365,
8747
+ "mmlu_eval_accuracy_computer_security": 0.2727272727272727,
8748
+ "mmlu_eval_accuracy_conceptual_physics": 0.3076923076923077,
8749
+ "mmlu_eval_accuracy_econometrics": 0.25,
8750
+ "mmlu_eval_accuracy_electrical_engineering": 0.3125,
8751
+ "mmlu_eval_accuracy_elementary_mathematics": 0.34146341463414637,
8752
+ "mmlu_eval_accuracy_formal_logic": 0.21428571428571427,
8753
+ "mmlu_eval_accuracy_global_facts": 0.4,
8754
+ "mmlu_eval_accuracy_high_school_biology": 0.375,
8755
+ "mmlu_eval_accuracy_high_school_chemistry": 0.5,
8756
+ "mmlu_eval_accuracy_high_school_computer_science": 0.5555555555555556,
8757
+ "mmlu_eval_accuracy_high_school_european_history": 0.5555555555555556,
8758
+ "mmlu_eval_accuracy_high_school_geography": 0.7727272727272727,
8759
+ "mmlu_eval_accuracy_high_school_government_and_politics": 0.5714285714285714,
8760
+ "mmlu_eval_accuracy_high_school_macroeconomics": 0.3953488372093023,
8761
+ "mmlu_eval_accuracy_high_school_mathematics": 0.20689655172413793,
8762
+ "mmlu_eval_accuracy_high_school_microeconomics": 0.34615384615384615,
8763
+ "mmlu_eval_accuracy_high_school_physics": 0.29411764705882354,
8764
+ "mmlu_eval_accuracy_high_school_psychology": 0.85,
8765
+ "mmlu_eval_accuracy_high_school_statistics": 0.43478260869565216,
8766
+ "mmlu_eval_accuracy_high_school_us_history": 0.5909090909090909,
8767
+ "mmlu_eval_accuracy_high_school_world_history": 0.6923076923076923,
8768
+ "mmlu_eval_accuracy_human_aging": 0.6521739130434783,
8769
+ "mmlu_eval_accuracy_human_sexuality": 0.3333333333333333,
8770
+ "mmlu_eval_accuracy_international_law": 0.8461538461538461,
8771
+ "mmlu_eval_accuracy_jurisprudence": 0.45454545454545453,
8772
+ "mmlu_eval_accuracy_logical_fallacies": 0.6111111111111112,
8773
+ "mmlu_eval_accuracy_machine_learning": 0.09090909090909091,
8774
+ "mmlu_eval_accuracy_management": 0.7272727272727273,
8775
+ "mmlu_eval_accuracy_marketing": 0.68,
8776
+ "mmlu_eval_accuracy_medical_genetics": 0.9090909090909091,
8777
+ "mmlu_eval_accuracy_miscellaneous": 0.6976744186046512,
8778
+ "mmlu_eval_accuracy_moral_disputes": 0.4473684210526316,
8779
+ "mmlu_eval_accuracy_moral_scenarios": 0.23,
8780
+ "mmlu_eval_accuracy_nutrition": 0.48484848484848486,
8781
+ "mmlu_eval_accuracy_philosophy": 0.5588235294117647,
8782
+ "mmlu_eval_accuracy_prehistory": 0.5142857142857142,
8783
+ "mmlu_eval_accuracy_professional_accounting": 0.16129032258064516,
8784
+ "mmlu_eval_accuracy_professional_law": 0.3588235294117647,
8785
+ "mmlu_eval_accuracy_professional_medicine": 0.6129032258064516,
8786
+ "mmlu_eval_accuracy_professional_psychology": 0.463768115942029,
8787
+ "mmlu_eval_accuracy_public_relations": 0.6666666666666666,
8788
+ "mmlu_eval_accuracy_security_studies": 0.48148148148148145,
8789
+ "mmlu_eval_accuracy_sociology": 0.7272727272727273,
8790
+ "mmlu_eval_accuracy_us_foreign_policy": 0.7272727272727273,
8791
+ "mmlu_eval_accuracy_virology": 0.4444444444444444,
8792
+ "mmlu_eval_accuracy_world_religions": 0.631578947368421,
8793
+ "mmlu_loss": 1.3430347967863705,
8794
+ "step": 9200
8795
  }
8796
  ],
8797
  "max_steps": 10000,
8798
  "num_train_epochs": 3,
8799
+ "total_flos": 1.133632921784746e+18,
8800
  "trial_name": null,
8801
  "trial_params": null
8802
  }
{checkpoint-7000 → checkpoint-9200}/training_args.bin RENAMED
File without changes